Showing 200 of total 396 results (show query)
christophsax
seasonal:R Interface to X-13-ARIMA-SEATS
Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. It offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. A graphical user interface can be used through the 'seasonalview' package. Uses the X-13-binaries from the 'x13binary' package.
Maintained by Christoph Sax. Last updated 17 days ago.
seasonal-adjustmenttime-series
75.7 match 120 stars 12.03 score 1.1k scripts 8 dependents
cran
NHLData:Scores for Every Season Since the Founding of the NHL in 1917
Each dataset contains scores for every game during a specific season of the NHL.
Maintained by D. Lukke Sweet. Last updated 8 years ago.
370.9 match 2.00 score 99 scripts
robjhyndman
forecast:Forecasting Functions for Time Series and Linear Models
Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Maintained by Rob Hyndman. Last updated 7 months ago.
forecastforecastingopenblascpp
33.4 match 1.1k stars 18.63 score 16k scripts 239 dependents
agbarnett
season:Seasonal Analysis of Health Data
Routines for the seasonal analysis of health data, including regression models, time-stratified case-crossover, plotting functions and residual checks, see Barnett and Dobson (2010) ISBN 978-3-642-10748-1. Thanks to Yuming Guo for checking the case-crossover code.
Maintained by Adrian Barnett. Last updated 3 years ago.
88.7 match 2 stars 5.85 score 70 scripts
business-science
timetk:A Tool Kit for Working with Time Series
Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'.
Maintained by Matt Dancho. Last updated 1 years ago.
coercioncoercion-functionsdata-miningdplyrforecastforecastingforecasting-modelsmachine-learningseries-decompositionseries-signaturetibbletidytidyquanttidyversetimetime-seriestimeseries
16.4 match 625 stars 14.15 score 4.0k scripts 16 dependents
rjdverse
rjd3toolkit:Utility Functions around 'JDemetra+ 3.0'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It provides functions allowing to model time series (create outlier regressors, user-defined calendar regressors, UCARIMA models...), to test the presence of trading days or seasonal effects and also to set specifications in pre-adjustment and benchmarking when using rjd3x13 or rjd3tramoseats.
Maintained by Tanguy Barthelemy. Last updated 5 months ago.
jdemetraseasonal-adjustmenttimeseriesopenjdk
32.2 match 5 stars 5.81 score 48 scripts 15 dependents
jaseziv
worldfootballR:Extract and Clean World Football (Soccer) Data
Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.
Maintained by Jason Zivkovic. Last updated 1 months ago.
fbreffootballfootball-datasoccer-datasports-datatransfermarktunderstat
17.7 match 506 stars 9.89 score 516 scripts 2 dependents
robeltakele
AquaBEHER:Estimation and Prediction of Wet Season Calendar and Soil Water Balance for Agriculture
Computes and integrates daily potential evapotranspiration (PET) and a soil water balance model. It allows users to estimate and predict the wet season calendar, including onset, cessation, and duration, based on an agroclimatic approach for a specified period. This functionality helps in managing agricultural water resources more effectively. For detailed methodologies, users can refer to Allen et al. (1998, ISBN:92-5-104219-5); Allen (2005, ISBN:9780784408056); Doorenbos and Pruitt (1975, ISBN:9251002797); Guo et al. (2016) <doi:10.1016/j.envsoft.2015.12.019>; Hargreaves and Samani (1985) <doi:10.13031/2013.26773>; Priestley and Taylor (1972) <https://journals.ametsoc.org/view/journals/apme/18/7/1520-0450_1979_018_0898_tptema_2_0_co_2.xml>.
Maintained by Robel Takele. Last updated 16 days ago.
growing-seasonseasonal-calendarsoil-moisturesoil-water-balance
28.0 match 10 stars 5.78 score 6 scripts
doehm
survivoR:Data from all Seasons of Survivor (US) TV Series in Tidy Format
Datasets detailing the results, castaways, and events of each season of Survivor for the US, Australia, South Africa, New Zealand, and the UK. This includes details on the cast, voting history, immunity and reward challenges, jury votes, boot order, advantage details, and episode ratings. Use this for analysis of trends and statistics of the game.
Maintained by Daniel Oehm. Last updated 2 days ago.
22.1 match 73 stars 7.08 score 94 scripts
bjw34032
waveslim:Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing
Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.
Maintained by Brandon Whitcher. Last updated 10 months ago.
19.8 match 3 stars 7.88 score 108 scripts 23 dependents
geobosh
sarima:Simulation and Prediction with Seasonal ARIMA Models
Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated (for the algebraic basis for this see <arXiv:2208.05055>, a paper on the methodology is being prepared).
Maintained by Georgi N. Boshnakov. Last updated 12 months ago.
arimakalman-filterreg-sarimasarimasarimaxseasonaltime-seriesxarimaopenblascpp
22.8 match 3 stars 6.71 score 112 scripts 1 dependents
ellisp
ggseas:'stats' for Seasonal Adjustment on the Fly with 'ggplot2'
Provides 'ggplot2' 'stats' that estimate seasonally adjusted series and rolling summaries such as rolling average on the fly for time series.
Maintained by Peter Ellis. Last updated 7 years ago.
21.5 match 74 stars 6.68 score 129 scriptsgeobosh
uroot:Unit Root Tests for Seasonal Time Series
Seasonal unit roots and seasonal stability tests. P-values based on response surface regressions are available for both tests. P-values based on bootstrap are available for seasonal unit root tests.
Maintained by Georgi N. Boshnakov. Last updated 11 months ago.
17.0 match 2 stars 7.88 score 512 scripts 11 dependents
tokami
TropFishR:Tropical Fisheries Analysis
A compilation of fish stock assessment methods for the analysis of length-frequency data in the context of data-poor fisheries. Includes methods and examples included in the FAO Manual by P. Sparre and S.C. Venema (1998), "Introduction to tropical fish stock assessment" (<http://www.fao.org/documents/card/en/c/9bb12a06-2f05-5dcb-a6ca-2d6dd3080f65/>), as well as other more recent methods.
Maintained by Tobias K. Mildenberger. Last updated 5 months ago.
assessmentfao-manualfishfish-stocks
14.9 match 25 stars 8.12 score 149 scripts
tidyverts
feasts:Feature Extraction and Statistics for Time Series
Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.
Maintained by Mitchell OHara-Wild. Last updated 4 months ago.
9.7 match 300 stars 12.38 score 1.4k scripts 7 dependents
jozefhajnala
nhlapi:A Minimum-Dependency 'R' Interface to the 'NHL' API
Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.
Maintained by Jozef Hajnala. Last updated 4 years ago.
19.6 match 29 stars 6.00 score 23 scripts
csids
cstime:Date and Time Functions for Public Health Purposes
Provides easy and consistent time conversion for public health purposes. The time conversion functions provided here are between date, ISO week, ISO yearweek, ISO year, calendar month/year, season, season week.
Maintained by Chi Zhang. Last updated 9 months ago.
23.4 match 4.95 score 7 scripts 2 dependents
hzambran
hydroTSM:Time Series Management and Analysis for Hydrological Modelling
S3 functions for management, analysis, interpolation and plotting of time series used in hydrology and related environmental sciences. In particular, this package is highly oriented to hydrological modelling tasks. The focus of this package has been put in providing a collection of tools useful for the daily work of hydrologists (although an effort was made to optimise each function as much as possible, functionality has had priority over speed). Bugs / comments / questions / collaboration of any kind are very welcomed, and in particular, datasets that can be included in this package for academic purposes.
Maintained by Mauricio Zambrano-Bigiarini. Last updated 1 months ago.
hydrologyhydrology-modelinghydrology-statisticalresourcewater-resources
11.1 match 45 stars 10.14 score 340 scripts 10 dependents
tbep-tech
wqtrends:Assess Water Quality Trends with Generalized Additive Models
Assess Water Quality Trends for Long-Term Monitoring Data in Estuaries using Generalized Additive Models following Wood (2017) <doi:10.1201/9781315370279> and Error Propagation with Mixed-Effects Meta-Analysis following Sera et al. (2019) <doi:10.1002/sim.8362>. Methods are available for model fitting, assessment of fit, annual and seasonal trend tests, and visualization of results.
Maintained by Marcus Beck. Last updated 6 days ago.
reportingsan-francisco-baytime-series-analysiswater-quality
20.8 match 10 stars 5.38 score 24 scripts
rosieluain
mort:Identifying Potential Mortalities and Expelled Tags in Aquatic Acoustic Telemetry Arrays
A toolkit for identifying potential mortalities and expelled tags in aquatic acoustic telemetry arrays. Designed for arrays with non-overlapping receivers.
Maintained by Rosie Smith. Last updated 6 months ago.
acoustic-telemetryaquaticmortality-estimation
20.6 match 4 stars 5.35 score 16 scripts
timginker
boiwsa:Seasonal Adjustment of Weekly Data
Perform seasonal adjustment of weekly data. The package provides a user-friendly interface for computing seasonally adjusted estimates of weekly data and includes functions for the creation of country-specific prior adjustment variables, as well as diagnostic tools to assess the quality of the adjustments. The method is described in more detail in Ginker (2023) <doi:10.13140/RG.2.2.12221.44000>.
Maintained by Tim Ginker. Last updated 1 months ago.
seasonal-adjustmentseasonalitytime-series-analysis
23.3 match 4 stars 4.48 score 3 scripts
zhaokg
Rbeast:Bayesian Change-Point Detection and Time Series Decomposition
Interpretation of time series data is affected by model choices. Different models can give different or even contradicting estimates of patterns, trends, and mechanisms for the same data--a limitation alleviated by the Bayesian estimator of abrupt change,seasonality, and trend (BEAST) of this package. BEAST seeks to improve time series decomposition by forgoing the "single-best-model" concept and embracing all competing models into the inference via a Bayesian model averaging scheme. It is a flexible tool to uncover abrupt changes (i.e., change-points), cyclic variations (e.g., seasonality), and nonlinear trends in time-series observations. BEAST not just tells when changes occur but also quantifies how likely the detected changes are true. It detects not just piecewise linear trends but also arbitrary nonlinear trends. BEAST is applicable to real-valued time series data of all kinds, be it for remote sensing, economics, climate sciences, ecology, and hydrology. Example applications include its use to identify regime shifts in ecological data, map forest disturbance and land degradation from satellite imagery, detect market trends in economic data, pinpoint anomaly and extreme events in climate data, and unravel system dynamics in biological data. Details on BEAST are reported in Zhao et al. (2019) <doi:10.1016/j.rse.2019.04.034>.
Maintained by Kaiguang Zhao. Last updated 6 months ago.
anomoly-detectionbayesian-time-seriesbreakpoint-detectionchangepoint-detectioninterrupted-time-seriesseasonality-analysisstructural-breakpointtechnical-analysistime-seriestime-series-decompositiontrendtrend-analysis
13.3 match 302 stars 7.63 score 89 scripts
eliocamp
metR:Tools for Easier Analysis of Meteorological Fields
Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
Maintained by Elio Campitelli. Last updated 21 days ago.
atmospheric-scienceggplot2visualization
8.3 match 144 stars 12.19 score 1000 scripts 22 dependents
roelandkindt
BiodiversityR:Package for Community Ecology and Suitability Analysis
Graphical User Interface (via the R-Commander) and utility functions (often based on the vegan package) for statistical analysis of biodiversity and ecological communities, including species accumulation curves, diversity indices, Renyi profiles, GLMs for analysis of species abundance and presence-absence, distance matrices, Mantel tests, and cluster, constrained and unconstrained ordination analysis. A book on biodiversity and community ecology analysis is available for free download from the website. In 2012, methods for (ensemble) suitability modelling and mapping were expanded in the package.
Maintained by Roeland Kindt. Last updated 2 months ago.
13.2 match 16 stars 7.42 score 390 scripts 2 dependentsrjdverse
RJDemetra:Interface to 'JDemetra+' Seasonal Adjustment Software
Interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.
Maintained by Alain Quartier-la-Tente. Last updated 10 days ago.
11.0 match 53 stars 8.67 score 128 scripts 5 dependents
nflverse
nflseedR:Functions to Efficiently Simulate and Evaluate NFL Seasons
A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.
Maintained by Sebastian Carl. Last updated 6 days ago.
football-simulationnflseason-simulations
15.0 match 23 stars 6.32 score 34 scripts 1 dependents
mwtoews
seas:Seasonal Analysis and Graphics, Especially for Climatology
Capable of deriving seasonal statistics, such as "normals", and analysis of seasonal data, such as departures. This package also has graphics capabilities for representing seasonal data, including boxplots for seasonal parameters, and bars for summed normals. There are many specific functions related to climatology, including precipitation normals, temperature normals, cumulative precipitation departures and precipitation interarrivals. However, this package is designed to represent any time-varying parameter with a discernible seasonal signal, such as found in hydrology and ecology.
Maintained by Mike Toews. Last updated 3 years ago.
25.7 match 8 stars 3.68 score 60 scriptschristophsax
seasonalview:Graphical User Interface for Seasonal Adjustment
A graphical user interface to the 'seasonal' package and 'X-13ARIMA-SEATS', the U.S. Census Bureau's seasonal adjustment software.
Maintained by Christoph Sax. Last updated 5 months ago.
seasonal-adjustmentshinytime-series
16.8 match 22 stars 5.59 score 105 scripts
mrc-ide
malariasimulation:An individual based model for malaria
Specifies the latest and greatest malaria model.
Maintained by Giovanni Charles. Last updated 28 days ago.
11.5 match 16 stars 8.17 score 146 scripts
jsocolar
flocker:Flexible Occupancy Estimation with Stan
Fit occupancy models in 'Stan' via 'brms'. The full variety of 'brms' formula-based effects structures are available to use in multiple classes of occupancy model, including single-season models, models with data augmentation for never-observed species, dynamic (multiseason) models with explicit colonization and extinction processes, and dynamic models with autologistic occupancy dynamics. Formulas can be specified for all relevant distributional terms, including detection and one or more of occupancy, colonization, extinction, and autologistic depending on the model type. Several important forms of model post-processing are provided. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Socolar & Mills (2023) <doi:10.1101/2023.10.26.564080>.
Maintained by Jacob B. Socolar. Last updated 2 months ago.
13.7 match 30 stars 6.78 score 20 scripts
hubbardalex
autostsm:Automatic Structural Time Series Models
Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.
Maintained by Alex Hubbard. Last updated 9 months ago.
26.1 match 3.55 score 29 scripts
eco-hydro
phenofit:Extract Remote Sensing Vegetation Phenology
The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And 'optimx' is used to select best optimization method for different curve fitting methods. Reference: Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.3.1, <doi:10.5281/zenodo.5150204>; Kong, D., Zhang, Y., Wang, D., Chen, J., & Gu, X. (2020). Photoperiod Explains the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636. <doi:10.1029/2020JG005636>; Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24; Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agric. For. Meteorol. 248, 408–417. <doi:10.1016/j.agrformet.2017.10.026>.
Maintained by Dongdong Kong. Last updated 1 months ago.
phenologyremote-sensingopenblascppopenmp
11.5 match 78 stars 7.71 score 332 scripts
jniedballa
camtrapR:Camera Trap Data Management and Preparation of Occupancy and Spatial Capture-Recapture Analyses
Management of and data extraction from camera trap data in wildlife studies. The package provides a workflow for storing and sorting camera trap photos (and videos), tabulates records of species and individuals, and creates detection/non-detection matrices for occupancy and spatial capture-recapture analyses with great flexibility. In addition, it can visualise species activity data and provides simple mapping functions with GIS export.
Maintained by Juergen Niedballa. Last updated 3 months ago.
occupancy-modelingspatial-capture-recapturewildlife
10.0 match 35 stars 8.65 score 178 scripts
billpetti
baseballr:Acquiring and Analyzing Baseball Data
Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.
Maintained by Saiem Gilani. Last updated 4 months ago.
baseballpitchfxsabermetricsstatcast
9.5 match 380 stars 8.98 score 582 scripts
hafen
stlplus:Enhanced Seasonal Decomposition of Time Series by Loess
Decompose a time series into seasonal, trend, and remainder components using an implementation of Seasonal Decomposition of Time Series by Loess (STL) that provides several enhancements over the STL method in the stats package. These enhancements include handling missing values, providing higher order (quadratic) loess smoothing with automated parameter choices, frequency component smoothing beyond the seasonal and trend components, and some basic plot methods for diagnostics.
Maintained by Ryan Hafen. Last updated 8 years ago.
12.2 match 66 stars 7.02 score 63 scripts 5 dependents
aqlt
ggdemetra:'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra'
Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by 'RJDemetra'. 'RJDemetra' is an 'R' interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks.
Maintained by Alain Quartier-la-Tente. Last updated 7 months ago.
14.0 match 12 stars 6.06 score 16 scripts 1 dependents
rtelmore
ISAR:Introduction to Sports Analytics using R (ISAR) Data
We provide data sets used in the forthcoming textbook "Introduction to Sports Analytics using R" by Elmore and Urbaczweski (2024). The package currently contains sixteen datasets and should be published in early 2024.
Maintained by Ryan Elmore. Last updated 8 months ago.
20.5 match 7 stars 4.02 score 3 scripts
openintrostat
openintro:Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs
Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.
Maintained by Mine Çetinkaya-Rundel. Last updated 3 months ago.
7.0 match 240 stars 11.39 score 6.0k scripts
prophet:Automatic Forecasting Procedure
Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.
Maintained by Sean Taylor. Last updated 5 months ago.
5.1 match 19k stars 15.53 score 976 scripts 13 dependents
mundl
lfstat:Calculation of Low Flow Statistics for Daily Stream Flow Data
The "Manual on Low-flow Estimation and Prediction", published by the World Meteorological Organisation (WMO), gives a comprehensive summary on how to analyse stream flow data focusing on low-flows. This packages provides functions to compute the described statistics and produces plots similar to the ones in the manual.
Maintained by Tobias Gauster. Last updated 2 years ago.
15.9 match 11 stars 4.94 score 159 scriptsgeobosh
pcts:Periodically Correlated and Periodically Integrated Time Series
Classes and methods for modelling and simulation of periodically correlated (PC) and periodically integrated time series. Compute theoretical periodic autocovariances and related properties of PC autoregressive moving average models. Some original methods including Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>, Boshnakov (1996) <doi:10.1111/j.1467-9892.1996.tb00281.x>.
Maintained by Georgi N. Boshnakov. Last updated 1 years ago.
par-modelsperiodicperiodic-modelspiar-modelsseasonaltime-seriestime-series-models
19.6 match 2 stars 4.00 score 3 scripts
rstudio
tfprobability:Interface to 'TensorFlow Probability'
Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow' that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU'). 'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers, variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.
Maintained by Tomasz Kalinowski. Last updated 3 years ago.
8.8 match 54 stars 8.63 score 221 scripts 3 dependents
jsta
wql:Exploring Water Quality Monitoring Data
Functions to assist in the processing and exploration of data from environmental monitoring programs. The package name stands for "water quality" and reflects the original focus on time series data for physical and chemical properties of water, as well as the biota. Intended for programs that sample approximately monthly, quarterly or annually at discrete stations, a feature of many legacy data sets. Most of the functions should be useful for analysis of similar-frequency time series regardless of the subject matter.
Maintained by Jemma Stachelek. Last updated 2 months ago.
9.8 match 12 stars 7.34 score 204 scripts 3 dependents
statmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
14.3 match 5 stars 4.94 score 544 scripts
jemus42
tRakt:Get Data from 'trakt.tv'
A wrapper for the <https://trakt.tv> API to retrieve data about shows and movies, including user ratings, credits and related metadata. Additional functions retrieve user-specific information including collections and history of watched items. A full API reference is available at <https://trakt.docs.apiary.io>.
Maintained by Lukas Burk. Last updated 4 hours ago.
11.4 match 22 stars 6.12 score 33 scripts
doi-usgs
EGRET:Exploration and Graphics for RivEr Trends
Statistics and graphics for streamflow history, water quality trends, and the statistical modeling algorithm: Weighted Regressions on Time, Discharge, and Season (WRTDS).
Maintained by Laura DeCicco. Last updated 4 months ago.
usgswater-qualitywater-quality-data
6.3 match 90 stars 10.72 score 362 scripts 1 dependents
biodiverse
unmarked:Models for Data from Unmarked Animals
Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
Maintained by Ken Kellner. Last updated 2 days ago.
5.0 match 4 stars 13.03 score 652 scripts 12 dependents
ouhscbbmc
Wats:Wrap Around Time Series Graphics
Wrap-around Time Series (WATS) plots for interrupted time series designs with seasonal patterns. Longitudinal trajectories are shown in both Cartesian and polar coordinates. In many scenarios, a WATS plot more clearly shows the existence and effect size of of an intervention. This package accompanies "Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs" by Rodgers, Beasley, & Schuelke (2014) <doi:10.1080/00273171.2014.946589>; see 'citation("Wats")' for details.
Maintained by Will Beasley. Last updated 21 days ago.
graphical-analysisoklahoma-city-bombingpublicationseasonaltime-series
10.5 match 7 stars 6.14 score 44 scripts
mikemeredith
wiqid:Quick and Dirty Estimates for Wildlife Populations
Provides simple, fast functions for maximum likelihood and Bayesian estimates of wildlife population parameters, suitable for use with simulated data or bootstraps. Early versions were indeed quick and dirty, but optional error-checking routines and meaningful error messages have been added. Includes single and multi-season occupancy, closed capture population estimation, survival, species richness and distance measures.
Maintained by Ngumbang Juat. Last updated 2 years ago.
13.0 match 2 stars 4.84 score 115 scripts 1 dependents
sportsdataverse
hoopR:Access Men's Basketball Play by Play Data
A utility to quickly obtain clean and tidy men's basketball play by play data. Provides functions to access live play by play and box score data from ESPN<https://www.espn.com> with shot locations when available. It is also a full NBA Stats API<https://www.nba.com/stats/> wrapper. It is also a scraping and aggregating interface for Ken Pomeroy's men's college basketball statistics website<https://kenpom.com>. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.
Maintained by Saiem Gilani. Last updated 1 years ago.
basketballcollege-basketballespnkenpomnbanba-analyticsnba-apinba-datanba-statisticsnba-statsnba-stats-apincaancaa-basketballncaa-bracketncaa-playersncaa-ratingsncaamsportsdataverse
9.1 match 91 stars 6.93 score 261 scriptsstatmanrobin
Lock5Data:Datasets for "Statistics: UnLocking the Power of Data"
Datasets for the third edition of "Statistics: Unlocking the Power of Data" by Lock^5 Includes version of datasets from earlier editions.
Maintained by Robin Lock. Last updated 4 years ago.
21.0 match 2.90 score 322 scripts
biostats-dev
ggsurveillance:Tools for Outbreak Investigation/Infectious Disease Surveillance
Create epicurves or epigantt charts in 'ggplot2'. Prepare data for visualisation or other reporting for infectious disease surveillance and outbreak investigation. Includes tidy functions to solve date based transformations for common reporting tasks, like (A) seasonal date alignment for respiratory disease surveillance, (B) date-based case binning based on specified time intervals like isoweek, epiweek, month and more, (C) automated detection and marking of the new year based on the date/datetime axis of the 'ggplot2'. An introduction on how to use epicurves can be found on the US CDC website (2012, <https://www.cdc.gov/training/quicklearns/epimode/index.html>).
Maintained by Alexander Bartel. Last updated 15 days ago.
epidemiologyinfectious-disease-surveillanceinfectious-diseasesoutbreaks
11.3 match 2 stars 5.31 score
viralemergence
epizootic:Spatially Explicit Population Models of Disease Transmission in Wildlife
This extension of the pattern-oriented modeling framework of the 'poems' package provides a collection of modules and functions customized for modeling disease transmission on a population scale in a spatiotemporally explicit manner. This includes seasonal time steps, dispersal functions that track disease state of dispersers, results objects that store disease states, and a population simulator that includes disease dynamics.
Maintained by July Pilowsky. Last updated 6 months ago.
10.9 match 4 stars 5.45 score 5 scriptsaqlt
ggdemetra3:'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'JDemetra+' 3.0
Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by the R interface to 'JDemetra+' 3.0.
Maintained by Alain Quartier-la-Tente. Last updated 3 months ago.
13.6 match 4 stars 4.26 score 8 scripts 1 dependents
tetratech
baytrends:Long Term Water Quality Trend Analysis
Enable users to evaluate long-term trends using a Generalized Additive Modeling (GAM) approach. The model development includes selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporation of hydrologic variability via either a river flow or salinity, the use of an intervention to deal with method or laboratory changes suspected to impact data values, and representation of left- and interval-censored data. The approach has been applied to water quality data in the Chesapeake Bay, a major estuary on the east coast of the United States to provide insights to a range of management- and research-focused questions. Methodology described in Murphy (2019) <doi:10.1016/j.envsoft.2019.03.027>.
Maintained by Erik W Leppo. Last updated 5 months ago.
8.5 match 12 stars 6.67 score 97 scripts
macroeconomicdata
dateutils:Date Utils
Utilities for mixed frequency data. In particular, use to aggregate and normalize tabular mixed frequency data, index dates to end of period, and seasonally adjust tabular data.
Maintained by Seth Leonard. Last updated 3 years ago.
data-processingeconometricstime-seriesopenblascpp
10.9 match 3 stars 5.17 score 49 scripts
lucasvenez
precintcon:Precipitation Intensity, Concentration and Anomaly Analysis
It contains functions to analyze the precipitation intensity, concentration and anomaly.
Maintained by Lucas Venezian Povoa. Last updated 9 years ago.
13.1 match 10 stars 4.28 score 38 scripts
matthieustigler
partsm:Periodic Autoregressive Time Series Models
Basic functions to fit and predict periodic autoregressive time series models. These models are discussed in the book P.H. Franses (1996) "Periodicity and Stochastic Trends in Economic Time Series", Oxford University Press. Data set analyzed in that book is also provided. NOTE: the package was orphaned during several years. It is now only maintained, but no major enhancements are expected, and the maintainer cannot provide any support.
Maintained by Matthieu Stigler. Last updated 4 years ago.
12.0 match 3 stars 4.57 score 25 scripts
asael697
bayesforecast:Bayesian Time Series Modeling with Stan
Fit Bayesian time series models using 'Stan' for full Bayesian inference. A wide range of distributions and models are supported, allowing users to fit Seasonal ARIMA, ARIMAX, Dynamic Harmonic Regression, GARCH, t-student innovation GARCH models, asymmetric GARCH, Random Walks, stochastic volatility models for univariate time series. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with typical visualization methods, information criteria such as loglik, AIC, BIC WAIC, Bayes factor and leave-one-out cross-validation methods. References: Hyndman (2017) <doi:10.18637/jss.v027.i03>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Maintained by Asael Alonzo Matamoros. Last updated 1 years ago.
bayesian-inferenceforecasting-modelsmcmcstantime-series-analysiscpp
7.8 match 45 stars 6.92 score 62 scripts
cbergmeir
Rlgt:Bayesian Exponential Smoothing Models with Trend Modifications
An implementation of a number of Global Trend models for time series forecasting that are Bayesian generalizations and extensions of some Exponential Smoothing models. The main differences/additions include 1) nonlinear global trend, 2) Student-t error distribution, and 3) a function for the error size, so heteroscedasticity. The methods are particularly useful for short time series. When tested on the well-known M3 dataset, they are able to outperform all classical time series algorithms. The models are fitted with MCMC using the 'rstan' package.
Maintained by Christoph Bergmeir. Last updated 8 months ago.
7.6 match 20 stars 7.05 score 31 scriptsbusiness-science
modeltime:The Tidymodels Extension for Time Series Modeling
The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Maintained by Matt Dancho. Last updated 5 months ago.
arimadata-sciencedeep-learningetsforecastingmachine-learningmachine-learning-algorithmsmodeltimeprophettbatstidymodelingtidymodelstimetime-seriestime-series-analysistimeseriestimeseries-forecasting
5.0 match 549 stars 10.57 score 1.1k scripts 7 dependents
ebird
ebirdst:Access and Analyze eBird Status and Trends Data Products
Tools for accessing and analyzing eBird Status and Trends Data Products (<https://science.ebird.org/en/status-and-trends>). eBird (<https://ebird.org/home>) is a global database of bird observations collected by member of the public. eBird Status and Trends uses these data to model global bird distributions, abundances, and population trends at a high spatial and temporal resolution.
Maintained by Matthew Strimas-Mackey. Last updated 20 days ago.
5.9 match 26 stars 8.85 score 228 scripts
bcgov
fasstr:Analyze, Summarize, and Visualize Daily Streamflow Data
The Flow Analysis Summary Statistics Tool for R, 'fasstr', provides various functions to tidy and screen daily stream discharge data, calculate and visualize various summary statistics and metrics, and compute annual trending and volume frequency analyses. It features useful function arguments for filtering of and handling dates, customizing data and metrics, and the ability to pull daily data directly from the Water Survey of Canada hydrometric database (<https://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>).
Maintained by Jon Goetz. Last updated 6 months ago.
bcgovforfrequency-analysishydathydrologystreamflowsummary-statisticstrendswater
6.8 match 57 stars 7.48 score 89 scripts
steffenmoritz
imputeTS:Time Series Missing Value Imputation
Imputation (replacement) of missing values in univariate time series. Offers several imputation functions and missing data plots. Available imputation algorithms include: 'Mean', 'LOCF', 'Interpolation', 'Moving Average', 'Seasonal Decomposition', 'Kalman Smoothing on Structural Time Series models', 'Kalman Smoothing on ARIMA models'. Published in Moritz and Bartz-Beielstein (2017) <doi:10.32614/RJ-2017-009>.
Maintained by Steffen Moritz. Last updated 3 years ago.
data-visualizationimputationimputation-algorithmimputetsmissing-datatime-seriescpp
4.1 match 162 stars 12.18 score 1.9k scripts 27 dependents
brry
berryFunctions:Function Collection Related to Plotting and Hydrology
Draw horizontal histograms, color scattered points by 3rd dimension, enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, fit multiple functions.
Maintained by Berry Boessenkool. Last updated 1 months ago.
5.3 match 13 stars 9.43 score 350 scripts 16 dependents
joongsup
uncmbb:UNC Men's Basketball Match Results Since 1949-1950 Season
Dataset contains select attributes for each match result since 1949-1950 season for UNC men's basketball team.
Maintained by Jay Lee. Last updated 4 years ago.
basketballcarolinacollegedukencaamnorth-carolinaunc
13.4 match 1 stars 3.53 score 68 scripts
eligurarie
cyclomort:Survival Modeling with a Periodic Hazard Function
Modeling periodic mortality (or other time-to event) processes from right-censored data. Given observations of a process with a known period (e.g. 365 days, 24 hours), functions determine the number, intensity, timing, and duration of peaks of periods of elevated hazard within a period. The underlying model is a mixed wrapped Cauchy function fitted using maximum likelihoods (details in Gurarie et al. (2020) <doi:10.1111/2041-210X.13305>). The development of these tools was motivated by the strongly seasonal mortality patterns observed in many wild animal populations, such that the respective periods of higher mortality can be identified as "mortality seasons".
Maintained by Eliezer Gurarie. Last updated 5 years ago.
11.8 match 2 stars 4.00 score 2 scripts
config-i1
smooth:Forecasting Using State Space Models
Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes ADAM (Svetunkov, 2023, <https://openforecast.org/adam/>), Exponential Smoothing (Hyndman et al., 2008, <doi: 10.1007/978-3-540-71918-2>), SARIMA (Svetunkov & Boylan, 2019 <doi: 10.1080/00207543.2019.1600764>), Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, <doi: 10.13140/RG.2.2.24986.29123>), Simple Moving Average (Svetunkov & Petropoulos, 2018 <doi: 10.1080/00207543.2017.1380326>) and several simulation functions. It also allows dealing with intermittent demand based on the iETS framework (Svetunkov & Boylan, 2019, <doi: 10.13140/RG.2.2.35897.06242>).
Maintained by Ivan Svetunkov. Last updated 2 days ago.
arimaarima-forecastingcesetsexponential-smoothingforecaststate-spacetime-seriesopenblascpp
3.9 match 90 stars 11.87 score 412 scripts 25 dependentsbusiness-science
sweep:Tidy Tools for Forecasting
Tidies up the forecasting modeling and prediction work flow, extends the 'broom' package with 'sw_tidy', 'sw_glance', 'sw_augment', and 'sw_tidy_decomp' functions for various forecasting models, and enables converting 'forecast' objects to "tidy" data frames with 'sw_sweep'.
Maintained by Matt Dancho. Last updated 1 years ago.
broomforecastforecasting-modelspredictiontidytidyversetimetime-seriestimeseries
4.9 match 155 stars 9.26 score 399 scripts 1 dependents
rpruim
fastR2:Foundations and Applications of Statistics Using R (2nd Edition)
Data sets and utilities to accompany the second edition of "Foundations and Applications of Statistics: an Introduction using R" (R Pruim, published by AMS, 2017), a text covering topics from probability and mathematical statistics at an advanced undergraduate level. R is integrated throughout, and access to all the R code in the book is provided via the snippet() function.
Maintained by Randall Pruim. Last updated 1 years ago.
7.6 match 13 stars 5.85 score 108 scripts
thibautjombart
adegenet:Exploratory Analysis of Genetic and Genomic Data
Toolset for the exploration of genetic and genomic data. Adegenet provides formal (S4) classes for storing and handling various genetic data, including genetic markers with varying ploidy and hierarchical population structure ('genind' class), alleles counts by populations ('genpop'), and genome-wide SNP data ('genlight'). It also implements original multivariate methods (DAPC, sPCA), graphics, statistical tests, simulation tools, distance and similarity measures, and several spatial methods. A range of both empirical and simulated datasets is also provided to illustrate various methods.
Maintained by Zhian N. Kamvar. Last updated 1 months ago.
3.5 match 182 stars 12.60 score 1.9k scripts 29 dependentsrjdverse
rjd3sts:State Space Framework and Structural Time Series with 'JDemetra+ 3.x'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It offers access to several functions on state space models and structural time series.
Maintained by Jean Palate. Last updated 8 months ago.
6.5 match 2 stars 6.64 score 25 scripts 4 dependents
sieste
SpecsVerification:Forecast Verification Routines for Ensemble Forecasts of Weather and Climate
A collection of forecast verification routines developed for the SPECS FP7 project. The emphasis is on comparative verification of ensemble forecasts of weather and climate.
Maintained by Stefan Siegert. Last updated 5 years ago.
13.7 match 1 stars 3.12 score 44 scripts 5 dependents
bayesiandemography
bage:Bayesian Estimation and Forecasting of Age-Specific Rates
Fast Bayesian estimation and forecasting of age-specific rates, probabilities, and means, based on 'Template Model Builder'.
Maintained by John Bryant. Last updated 2 months ago.
5.9 match 3 stars 7.30 score 39 scriptsaqlt
rjdqa:Quality Assessment for Seasonal Adjustment
Add-in to the 'RJDemetra' package on seasonal adjustments. It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment.
Maintained by Alain Quartier-la-Tente. Last updated 4 months ago.
jdemetraquality-assessmentopenjdk
11.0 match 2 stars 3.85 score 8 scriptsrobjhyndman
stR:Seasonal Trend Decomposition Using Regression
Methods for decomposing seasonal data: STR (a Seasonal-Trend time series decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can also be used for forecasting.
Maintained by Rob Hyndman. Last updated 2 months ago.
6.0 match 7 stars 7.02 score 1.3k scripts 2 dependents
trnnick
tsutils:Time Series Exploration, Modelling and Forecasting
Includes: (i) tests and visualisations that can help the modeller explore time series components and perform decomposition; (ii) modelling shortcuts, such as functions to construct lagmatrices and seasonal dummy variables of various forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the design of the forecasting process, such as ABC-XYZ analyses; and (v) "quality of life" functions, such as treating time series for trailing and leading values.
Maintained by Nikolaos Kourentzes. Last updated 1 years ago.
5.4 match 12 stars 7.78 score 472 scripts 18 dependents
lightbluetitan
usdatasets:A Comprehensive Collection of U.S. Datasets
Provides a diverse collection of U.S. datasets encompassing various fields such as crime, economics, education, finance, energy, healthcare, and more. It serves as a valuable resource for researchers and analysts seeking to perform in-depth analyses and derive insights from U.S.-specific data.
Maintained by Renzo Caceres Rossi. Last updated 5 months ago.
7.0 match 7 stars 5.99 score 141 scripts
xavi-rp
LPDynR:Land Productivity Dynamics Indicator
It uses 'phenological' and productivity-related variables derived from time series of vegetation indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing productivity. See www.sciencedirect.com/science/article/pii/S1470160X21010517/ for a description of the methods used in the package to calculate the indicator.
Maintained by Xavier Rotllan-Puig. Last updated 6 months ago.
copernicus-global-land-serviceearth-observationland-degradationland-productivityvegetation
8.5 match 8 stars 4.90 score 5 scripts
fawda123
WRTDStidal:Weighted Regression for Water Quality Evaluation in Tidal Waters
An adaptation for estuaries (tidal waters) of weighted regression on time, discharge, and season to evaluate trends in water quality time series. Please see Beck and Hagy (2015) <doi:10.1007/s10666-015-9452-8> for details.
Maintained by Marcus W. Beck. Last updated 1 years ago.
7.7 match 4 stars 5.38 score 119 scripts
alsabtay
ATAforecasting:Automatic Time Series Analysis and Forecasting using the Ata Method
The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative to exponential smoothing (described in Yapar (2016) <doi:10.15672/HJMS.201614320580>, Yapar et al. (2017) <doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal). This methodology performed well on the M3 and M4-competition data. This package was written based on Ali Sabri Taylan’s PhD dissertation.
Maintained by Ali Sabri Taylan. Last updated 2 years ago.
ataataforecastingfableforecastforecastingtime-seriescpp
10.5 match 5 stars 3.88 score 4 scripts 1 dependents
ovvo-financial
NNS:Nonlinear Nonparametric Statistics
Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Maintained by Fred Viole. Last updated 6 days ago.
clusteringeconometricsmachine-learningnonlinearnonparametricpartial-momentsstatisticstime-seriescpp
3.7 match 71 stars 10.96 score 66 scripts 3 dependents
x13org
x13binary:Provide the 'x13ashtml' Seasonal Adjustment Binary
The US Census Bureau provides a seasonal adjustment program now called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau offers both source and binary versions -- which this package integrates for use by other R packages.
Maintained by Dirk Eddelbuettel. Last updated 8 months ago.
5.2 match 10 stars 7.50 score 16 scripts 10 dependents
alexwaterboybezzina
CalcThemAll.PRM:Calculate Pesticide Risk Metric (PRM) Values from Multiple Pesticides...Calc Them All
Contains functions which can be used to calculate Pesticide Risk Metric values in aquatic environments from concentrations of multiple pesticides with known species sensitive distributions (SSDs). Pesticides provided by this package have all be validated however if the user has their own pesticides with SSD values they can append them to the pesticide_info table to include them in estimates.
Maintained by Alexander Bezzina. Last updated 11 months ago.
8.2 match 2 stars 4.78 scoresportsdataverse
wehoop:Access Women's Basketball Play by Play Data
A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.
Maintained by Saiem Gilani. Last updated 8 months ago.
college-basketballespnespn-statsncaancaa-basketballprofessional-basketball-datasportsdataversewnbawnba-playerswnba-statswomens-basketball
7.3 match 28 stars 5.36 score 54 scripts
bayesball
LearnBayes:Learning Bayesian Inference
Contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
Maintained by Jim Albert. Last updated 7 years ago.
3.4 match 38 stars 11.34 score 690 scripts 31 dependents
danielollech
seastests:Seasonality Tests
An overall test for seasonality of a given time series in addition to a set of individual seasonality tests as described by Ollech and Webel (forthcoming): An overall seasonality test. Bundesbank Discussion Paper.
Maintained by Daniel Ollech. Last updated 3 years ago.
12.4 match 2 stars 3.10 score 105 scripts 2 dependentsnflverse
nflfastR:Functions to Efficiently Access NFL Play by Play Data
A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.
Maintained by Ben Baldwin. Last updated 2 months ago.
american-footballfootball-datanflnflstatsnflversesports-analytics
3.7 match 442 stars 10.40 score 596 scripts 3 dependents
kwstat
agridat:Agricultural Datasets
Datasets from books, papers, and websites related to agriculture. Example graphics and analyses are included. Data come from small-plot trials, multi-environment trials, uniformity trials, yield monitors, and more.
Maintained by Kevin Wright. Last updated 28 days ago.
3.4 match 125 stars 11.02 score 1.7k scripts 2 dependents
poissonconsulting
gsdd:Calculate Growing Season Degree Days from Water Temperature Data
Calculates Growing Season Degree Days (GSDD), Growing Degree Days (GDD) and the Growing Seasons (GSS) from water temperature data. GSSD is a water temperature metric that is a useful predictor of age-0 trout size at the beginning of winter. It is the accumulated thermal units (in C) during the growing season based on the mean daily water temperature values. GDD is the GSSD to a particular date.
Maintained by Joe Thorley. Last updated 22 days ago.
11.0 match 2 stars 3.38 score 5 scripts
borisberanger
ExtremalDep:Extremal Dependence Models
A set of procedures for parametric and non-parametric modelling of the dependence structure of multivariate extreme-values is provided. The statistical inference is performed with non-parametric estimators, likelihood-based estimators and Bayesian techniques. It adapts the methodologies of Beranger and Padoan (2015) <doi:10.48550/arXiv.1508.05561>, Marcon et al. (2016) <doi:10.1214/16-EJS1162>, Marcon et al. (2017) <doi:10.1002/sta4.145>, Marcon et al. (2017) <doi:10.1016/j.jspi.2016.10.004> and Beranger et al. (2021) <doi:10.1007/s10687-019-00364-0>. This package also allows for the modelling of spatial extremes using flexible max-stable processes. It provides simulation algorithms and fitting procedures relying on the Stephenson-Tawn likelihood as per Beranger at al. (2021) <doi:10.1007/s10687-020-00376-1>.
Maintained by Simone Padoan. Last updated 3 months ago.
11.0 match 3.30 score 1 scripts
ffverse
ffsimulator:Simulate Fantasy Football Seasons
Uses bootstrap resampling to run fantasy football season simulations supported by historical rankings and 'nflfastR' data, calculating optimal lineups, and returning aggregated results.
Maintained by Tan Ho. Last updated 6 months ago.
7.0 match 17 stars 5.17 score 44 scripts
aparamon
mar1s:Multiplicative AR(1) with Seasonal Processes
Multiplicative AR(1) with Seasonal is a stochastic process model built on top of AR(1). The package provides the following procedures for MAR(1)S processes: fit, compose, decompose, advanced simulate and predict.
Maintained by Andrey Paramonov. Last updated 7 years ago.
13.3 match 2.70 score 8 scripts
jverzani
UsingR:Data Sets, Etc. for the Text "Using R for Introductory Statistics", Second Edition
A collection of data sets to accompany the textbook "Using R for Introductory Statistics," second edition.
Maintained by John Verzani. Last updated 3 years ago.
7.0 match 1 stars 4.97 score 1.4k scriptsdanielollech
dsa:Seasonal Adjustment of Daily Time Series
Seasonal- and calendar adjustment of time series with daily frequency using the DSA approach developed by Ollech, Daniel (2018): Seasonal adjustment of daily time series. Bundesbank Discussion Paper 41/2018.
Maintained by Daniel Ollech. Last updated 4 years ago.
10.5 match 1 stars 3.19 score 52 scripts 1 dependents
mapme-initiative
mapme.biodiversity:Efficient Monitoring of Global Biodiversity Portfolios
Biodiversity areas, especially primary forest, serve a multitude of functions for local economy, regional functionality of the ecosystems as well as the global health of our planet. Recently, adverse changes in human land use practices and climatic responses to increased greenhouse gas emissions, put these biodiversity areas under a variety of different threats. The present package helps to analyse a number of biodiversity indicators based on freely available geographical datasets. It supports computational efficient routines that allow the analysis of potentially global biodiversity portfolios. The primary use case of the package is to support evidence based reporting of an organization's effort to protect biodiversity areas under threat and to identify regions were intervention is most duly needed.
Maintained by Darius A. Görgen. Last updated 3 months ago.
environmenteogismapmespatialsustainability
3.6 match 35 stars 9.24 score 287 scripts
critical-infrastructure-systems-lab
reservoir:Tools for Analysis, Design, and Operation of Water Supply Storages
Measure single-storage water supply system performance using resilience, reliability, and vulnerability metrics; assess storage-yield- reliability relationships; determine no-fail storage with sequent peak analysis; optimize release decisions for water supply, hydropower, and multi-objective reservoirs using deterministic and stochastic dynamic programming; generate inflow replicates using parametric and non-parametric models; evaluate inflow persistence using the Hurst coefficient.
Maintained by Sean Turner. Last updated 4 years ago.
hydrologyreservoirsimulationwater-resources
8.3 match 28 stars 4.00 score 18 scriptscran
trend:Non-Parametric Trend Tests and Change-Point Detection
The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
Maintained by Thorsten Pohlert. Last updated 1 years ago.
6.1 match 3 stars 5.31 score 9 dependents
rnuske
vegperiod:Determine Thermal Vegetation Periods
Collection of common methods to determine growing season length in a simple manner. Start and end dates of the vegetation periods are calculated solely based on daily mean temperatures and the day of the year.
Maintained by Robert Nuske. Last updated 9 months ago.
dwdgrowing-seasonvegetation-period
8.0 match 7 stars 4.02 score 9 scripts 1 dependents
celevitz
topChef:Top Chef Data
Several datasets which describe the chef contestants in Top Chef, the challenges that they compete in, and the results of those challenges. This data is useful for practicing data wrangling, graphing, and analyzing how each season of Top Chef played out.
Maintained by Levitz Carly E. Last updated 11 days ago.
5.4 match 3 stars 5.97 score 26 scripts
weecology
portalr:Create Useful Summaries of the Portal Data
Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahuan desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
Maintained by Glenda M. Yenni. Last updated 4 months ago.
community-ecologyecologysmall-mammal-trapping
4.0 match 11 stars 7.64 score 63 scripts
benjaminhlina
ecotox:Analysis of Ecotoxicology
A simple approach to using a probit or logit analysis to calculate lethal concentration (LC) or time (LT) and the appropriate fiducial confidence limits desired for selected LC or LT for ecotoxicology studies (Finney 1971; Wheeler et al. 2006; Robertson et al. 2007). The simplicity of 'ecotox' comes from the syntax it implies within its functions which are similar to functions like glm() and lm(). In addition to the simplicity of the syntax, a comprehensive data frame is produced which gives the user a predicted LC or LT value for the desired level and a suite of important parameters such as fiducial confidence limits and slope. Finney, D.J. (1971, ISBN: 052108041X); Wheeler, M.W., Park, R.M., and Bailer, A.J. (2006) <doi:10.1897/05-320R.1>; Robertson, J.L., Savin, N.E., Russell, R.M., and Preisler, H.K. (2007, ISBN: 0849323312).
Maintained by Benjamin L Hlina. Last updated 2 months ago.
biologydose-response-modelinglogitprobittoxicology
6.7 match 3 stars 4.50 score 10 scripts
hturner
PlackettLuce:Plackett-Luce Models for Rankings
Functions to prepare rankings data and fit the Plackett-Luce model jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in the implementation. Disconnected/weakly connected networks implied by the rankings may be handled by adding pseudo-rankings with a hypothetical item. Optionally, a multivariate normal prior may be set on the log-worth parameters and ranker reliabilities may be incorporated as proposed by Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a posteriori estimation is used when priors are set. Methods are provided to estimate standard errors or quasi-standard errors for inference as well as to fit Plackett-Luce trees. See the package website or vignette for further details.
Maintained by Heather Turner. Last updated 2 years ago.
plackett-luce-modelspreferencesrankingrankings-datastatistical-models
3.8 match 20 stars 7.97 score 86 scripts 3 dependents
nickbond
hydrostats:Hydrologic Indices for Daily Time Series Data
Calculates a suite of hydrologic indices for daily time series data that are widely used in hydrology and stream ecology.
Maintained by Nick Bond. Last updated 3 years ago.
5.0 match 26 stars 5.71 score 65 scripts 1 dependents
pbiecek
PogromcyDanych:DataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People
The data sets used in the online course ,,PogromcyDanych''. You can process data in many ways. The course Data Crunchers will introduce you to this variety. For this reason we will work on datasets of different size (from several to several hundred thousand rows), with various level of complexity (from two to two thousand columns) and prepared in different formats (text data, quantitative data and qualitative data). All of these data sets were gathered in a single big package called PogromcyDanych to facilitate access to them. It contains all sorts of data sets such as data about offer prices of cars, results of opinion polls, information about changes in stock market indices, data about names given to newborn babies, ski jumping results or information about outcomes of breast cancer patients treatment.
Maintained by Przemyslaw Biecek. Last updated 2 years ago.
5.3 match 8 stars 5.41 score 215 scripts 1 dependentsdoehm
alone:Datasets from the Survival TV Series Alone
A collection of datasets on the Alone survival TV series in tidy format. Included in the package are 4 datasets detailing the survivors, their loadouts, episode details and season information.
Maintained by Daniel Oehm. Last updated 6 months ago.
6.5 match 15 stars 4.35 score 10 scripts
bsnatr
tswge:Time Series for Data Science
Accompanies the texts Time Series for Data Science with R by Woodward, Sadler and Robertson & Applied Time Series Analysis with R, 2nd edition by Woodward, Gray, and Elliott. It is helpful for data analysis and for time series instruction.
Maintained by Bivin Sadler. Last updated 2 years ago.
10.5 match 2.70 score 496 scripts
akarl46556
mvglmmRank:Multivariate Generalized Linear Mixed Models for Ranking Sports Teams
Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018) <doi:10.48550/arXiv.1710.05284>, Karl, Yang, and Lohr (2014) <doi:10.1016/j.csda.2013.11.019>, and by Karl (2012) <doi:10.1515/1559-0410.1471>. Karl and Zimmerman <doi:10.1016/j.jspi.2020.06.004> use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.
Maintained by Andrew T. Karl. Last updated 2 years ago.
20.7 match 2 stars 1.34 score 11 scripts
thiyangt
seer:Feature-Based Forecast Model Selection
A novel meta-learning framework for forecast model selection using time series features. Many applications require a large number of time series to be forecast. Providing better forecasts for these time series is important in decision and policy making. We propose a classification framework which selects forecast models based on features calculated from the time series. We call this framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping that relates the features of time series to the best forecast model using a random forest. 'seer' package is the implementation of the FFORMS algorithm. For more details see our paper at <https://www.monash.edu/business/econometrics-and-business-statistics/research/publications/ebs/wp06-2018.pdf>.
Maintained by Thiyanga Talagala. Last updated 2 years ago.
5.2 match 78 stars 5.31 score 52 scripts
juergenknauer
bigleaf:Physical and Physiological Ecosystem Properties from Eddy Covariance Data
Calculation of physical (e.g. aerodynamic conductance, surface temperature), and physiological (e.g. canopy conductance, water-use efficiency) ecosystem properties from eddy covariance data and accompanying meteorological measurements. Calculations assume the land surface to behave like a 'big-leaf' and return bulk ecosystem/canopy variables.
Maintained by Juergen Knauer. Last updated 8 months ago.
3.8 match 7.23 score 124 scripts 17 dependents
oteros
AeRobiology:A Computational Tool for Aerobiological Data
Different tools for managing databases of airborne particles, elaborating the main calculations and visualization of results. In a first step, data are checked using tools for quality control and all missing gaps are completed. Then, the main parameters of the pollen season are calculated and represented graphically. Multiple graphical tools are available: pollen calendars, phenological plots, time series, tendencies, interactive plots, abundance plots...
Maintained by "Jose Oteros". Last updated 6 years ago.
10.9 match 1 stars 2.46 score 29 scriptsthibautjombart
treespace:Statistical Exploration of Landscapes of Phylogenetic Trees
Tools for the exploration of distributions of phylogenetic trees. This package includes a 'shiny' interface which can be started from R using treespaceServer(). For further details see Jombart et al. (2017) <DOI:10.1111/1755-0998.12676>.
Maintained by Michelle Kendall. Last updated 2 years ago.
3.6 match 28 stars 7.39 score 63 scriptsrobjhyndman
tsfeatures:Time Series Feature Extraction
Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.
Maintained by Rob Hyndman. Last updated 8 months ago.
2.3 match 254 stars 11.47 score 268 scripts 22 dependents
smac-group
simts:Time Series Analysis Tools
A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi: 10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.
Maintained by Stéphane Guerrier. Last updated 2 years ago.
rcpprcpparmadillosimulationtime-seriestimeseriestimeseries-dataopenblascpp
3.4 match 15 stars 7.68 score 59 scripts 4 dependents
petolau
TSrepr:Time Series Representations
Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.
Maintained by Peter Laurinec. Last updated 5 years ago.
data-analysisdata-miningdata-mining-algorithmsdata-sciencerepresentationtime-seriestime-series-analysistime-series-classificationtime-series-clusteringtime-series-data-miningtime-series-representationscpp
3.6 match 97 stars 7.23 score 117 scripts
f-silva-archaeo
skyscapeR:Data Analysis and Visualization for Skyscape Archaeology
Data reduction, visualization and statistical analysis of measurements of orientation of archaeological structures, following Silva (2020) <doi:10.1016/j.jas.2020.105138>.
Maintained by Silva Fabio. Last updated 6 months ago.
4.9 match 5 stars 5.31 score 41 scripts
nowosad
pollen:Analysis of Aerobiological Data
Supports analysis of aerobiological data. Available features include determination of pollen season limits, replacement of outliers (Kasprzyk and Walanus (2014) <doi:10.1007/s10453-014-9332-8>), calculation of growing degree days (Baskerville and Emin (1969) <doi:10.2307/1933912>), and determination of the base temperature for growing degree days (Yang et al. (1995) <doi:10.1016/0168-1923(94)02185-M).
Maintained by Jakub Nowosad. Last updated 2 years ago.
aerobiological-dataaerobiologygddgrowing-degree-dayspollen
5.3 match 3 stars 4.89 score 26 scripts
epiverse-trace
epidemics:Composable Epidemic Scenario Modelling
A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.
Maintained by Rosalind Eggo. Last updated 9 months ago.
decision-supportepidemic-modellingepidemic-simulationsepidemiologyepiverseinfectious-disease-dynamicsmodel-librarynon-pharmaceutical-interventionsrcpprcppeigenscenario-analysisvaccinationcpp
3.4 match 9 stars 7.48 score 59 scripts
flr
FLBEIA:Bio-Economic Impact Assessment of Management Strategies using FLR
A simulation toolbox that describes a fishery system under a Management Strategy Estrategy approach. The objective of the model is to facilitate the Bio-Economic evaluation of Management strategies. It is multistock, multifleet and seasonal. The simulation is divided in 2 main blocks, the Operating Model (OM) and the Management Procedure (MP). In turn, each of these two blocks is divided in 3 components: the biological, the fleets and the covariables on the one hand, and the observation, the assessment and the advice on the other.
Maintained by FLBEIA Team. Last updated 6 days ago.
4.3 match 11 stars 5.97 score 156 scripts
steve-the-bayesian
bsts:Bayesian Structural Time Series
Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.
Maintained by Steven L. Scott. Last updated 1 years ago.
3.9 match 33 stars 6.54 score 338 scripts 3 dependentsnflverse
nflreadr:Download 'nflverse' Data
A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.
Maintained by Tan Ho. Last updated 4 months ago.
nflnflfastrnflversesports-data
2.0 match 66 stars 12.46 score 476 scripts 10 dependents
sbgraves237
Ecdat:Data Sets for Econometrics
Data sets for econometrics, including political science.
Maintained by Spencer Graves. Last updated 4 months ago.
3.4 match 2 stars 7.25 score 740 scripts 3 dependents
sinhrks
ggfortify:Data Visualization Tools for Statistical Analysis Results
Unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using 'ggplot2'.
Maintained by Yuan Tang. Last updated 9 months ago.
1.7 match 529 stars 14.49 score 9.1k scripts 22 dependents
kloke
npsm:Nonparametric Statistical Methods
Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics. Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems. Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.
Maintained by John Kloke. Last updated 9 months ago.
7.0 match 3.47 score 59 scripts
haghbinh
Rsfar:Seasonal Functional Autoregressive Models
This is a collection of functions designed for simulating, estimating and forecasting seasonal functional autoregressive time series of order one. These methods are addressed in the manuscript: <https://www.monash.edu/business/ebs/research/publications/ebs/wp16-2019.pdf>.
Maintained by Hossein Haghbin. Last updated 4 years ago.
7.1 match 5 stars 3.40 score
agrocares
OBIC:Calculate the Open Bodem Index (OBI) Score
The Open Bodem Index (OBI) is a method to evaluate the quality of soils of agricultural fields in The Netherlands and the sustainability of the current agricultural practices. The OBI score is based on four main criteria: chemical, physical, biological and management, which consist of more than 21 indicators. By providing results of a soil analysis and management info the 'OBIC' package can be use to calculate he scores, indicators and derivatives that are used by the OBI. More information about the Open Bodem Index can be found at <https://openbodemindex.nl/>.
Maintained by Sven Verweij. Last updated 6 months ago.
3.5 match 11 stars 6.82 score 20 scripts
bluegreen-labs
snotelr:Calculate and Visualize 'SNOTEL' Snow Data and Seasonality
Programmatic interface to the 'SNOTEL' snow data (<https://www.nrcs.usda.gov/programs-initiatives/sswsf-snow-survey-and-water-supply-forecasting-program>). Provides easy downloads of snow data into your R work space or a local directory. Additional post-processing routines to extract snow season indexes are provided.
Maintained by Koen Hufkens. Last updated 5 months ago.
climate-datadata-retrievalprecipitation-datasnotelsnow
3.4 match 16 stars 6.84 score 57 scriptscran
s2dv:A Set of Common Tools for Seasonal to Decadal Verification
The advanced version of package 's2dverification'. It is intended for 'seasonal to decadal' (s2d) climate forecast verification, but it can also be used in other kinds of forecasts or general climate analysis. This package is specially designed for the comparison between the experimental and observational datasets. The functionality of the included functions covers from data retrieval, data post-processing, skill scores against observation, to visualization. Compared to 's2dverification', 's2dv' is more compatible with the package 'startR', able to use multiple cores for computation and handle multi-dimensional arrays with a higher flexibility. The CDO version used in development is 1.9.8.
Maintained by Ariadna Batalla. Last updated 5 months ago.
11.9 match 1.95 score 3 dependentscran
TSA:Time Series Analysis
Contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.
Maintained by Kung-Sik Chan. Last updated 3 years ago.
5.1 match 2 stars 4.47 score 5 dependents
lmiratrix
simITS:Analysis via Simulation of Interrupted Time Series (ITS) Data
Uses simulation to create prediction intervals for post-policy outcomes in interrupted time series (ITS) designs, following Miratrix (2020) <arXiv:2002.05746>. This package provides methods for fitting ITS models with lagged outcomes and variables to account for temporal dependencies. It then conducts inference via simulation, simulating a set of plausible counterfactual post-policy series to compare to the observed post-policy series. This package also provides methods to visualize such data, and also to incorporate seasonality models and smoothing and aggregation/summarization. This work partially funded by Arnold Ventures in collaboration with MDRC.
Maintained by Luke Miratrix. Last updated 2 years ago.
5.3 match 2 stars 4.30 scorecran
lunar:Calculate Lunar Phase & Distance, Seasons and Related Environmental Factors
Provides functions to calculate lunar and other related environmental covariates.
Maintained by Emmanuel Lazaridis. Last updated 3 years ago.
11.6 match 1.95 score 1 dependents
flare-forecast
ropenmeteo:Wrappers for 'Open-Meteo' API
Wrappers for the Application Programming Interface from the <https://open-meteo.com> project along with helper functions. The <https://open-meteo.com> project streamlines access to a range of publicly historical and forecast meteorology data from agencies across the world.
Maintained by Quinn Thomas. Last updated 7 months ago.
4.8 match 4.62 score 14 scripts
lozalojo
mem:The Moving Epidemic Method
The Moving Epidemic Method, created by T Vega and JE Lozano (2012, 2015) <doi:10.1111/j.1750-2659.2012.00422.x>, <doi:10.1111/irv.12330>, allows the weekly assessment of the epidemic and intensity status to help in routine respiratory infections surveillance in health systems. Allows the comparison of different epidemic indicators, timing and shape with past epidemics and across different regions or countries with different surveillance systems. Also, it gives a measure of the performance of the method in terms of sensitivity and specificity of the alert week.
Maintained by Jose E. Lozano. Last updated 2 years ago.
3.5 match 14 stars 6.24 score 82 scripts 1 dependentstidyverts
fabletools:Core Tools for Packages in the 'fable' Framework
Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Maintained by Mitchell OHara-Wild. Last updated 1 months ago.
1.8 match 91 stars 12.18 score 396 scripts 18 dependents
neuropsychology
psycho:Efficient and Publishing-Oriented Workflow for Psychological Science
The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.
Maintained by Dominique Makowski. Last updated 4 years ago.
apaapa6bayesiancorrelationformatinterpretationmixed-modelsneurosciencepsychopsychologyrstanarmstatistics
2.0 match 149 stars 10.86 score 628 scripts 5 dependents
echasnovski
comperes:Manage Competition Results
Tools for storing and managing competition results. Competition is understood as a set of games in which players gain some abstract scores. There are two ways for storing results: in long (one row per game-player) and wide (one row per game with fixed amount of players) formats. This package provides functions for creation and conversion between them. Also there are functions for computing their summary and Head-to-Head values for players. They leverage grammar of data manipulation from 'dplyr'.
Maintained by Evgeni Chasnovski. Last updated 2 years ago.
3.4 match 8 stars 6.28 score 40 scripts 1 dependentsrjdverse
rjd3x13:Seasonal Adjustment with X-13 in 'JDemetra+ 3.x'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It offers full acces to options and outputs of X-13, including RegARIMA modelling (automatic ARIMA model with outlier detection and trading days adjustment) and X-11 decomposition.
Maintained by Tanguy Barthelemy. Last updated 5 months ago.
4.7 match 5 stars 4.53 score 8 scripts 3 dependentsrjdverse
rjd3tramoseats:Seasonal Adjustment with TRAMO-SEATS in 'JDemetra+ 3.x'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It offers full acces to options and outputs of TRAMO-SEATS (Time series Regression with ARIMA noise, Missing values and Outliers - Signal Extraction in ARIMA Time Series), including TRAMO modelling (automatic ARIMA model with outlier detection and trading days adjustment).
Maintained by Tanguy Barthelemy. Last updated 5 months ago.
4.7 match 5 stars 4.51 score 12 scripts 3 dependents
swampthingpaul
NADA2:Data Analysis for Censored Environmental Data
Contains methods described by Dennis Helsel in his book "Statistics for Censored Environmental Data using Minitab and R" (2011) and courses and videos at <https://practicalstats.com>. This package adds new functions to the `NADA` Package.
Maintained by Paul Julian. Last updated 6 months ago.
3.5 match 15 stars 6.16 score 16 scripts
dwarton
ecostats:Code and Data Accompanying the Eco-Stats Text (Warton 2022)
Functions and data supporting the Eco-Stats text (Warton, 2022, Springer), and solutions to exercises. Functions include tools for using simulation envelopes in diagnostic plots, and a function for diagnostic plots of multivariate linear models. Datasets mentioned in the package are included here (where not available elsewhere) and there is a vignette for each chapter of the text with solutions to exercises.
Maintained by David Warton. Last updated 1 years ago.
3.2 match 8 stars 6.58 score 53 scripts
alexkowa
EnvStats:Package for Environmental Statistics, Including US EPA Guidance
Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).
Maintained by Alexander Kowarik. Last updated 17 days ago.
1.7 match 26 stars 12.80 score 2.4k scripts 46 dependentsflr
mse:Tools for Running Management Strategy Evaluations using FLR
A set of functions and methods to enable the development and running of Management Strategy Evaluation (MSE) analyses, using the FLR packages and classes and the a4a methods and algorithms.
Maintained by Iago Mosqueira. Last updated 22 days ago.
3.0 match 4 stars 7.04 score 137 scripts 3 dependents
reinhardfurrer
spam:SPArse Matrix
Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.
Maintained by Reinhard Furrer. Last updated 2 months ago.
2.3 match 1 stars 9.26 score 420 scripts 433 dependents
bemts-hhs
traumar:Calculate Metrics for Trauma System Performance
Hospitals, hospital systems, and even trauma systems that provide care to injured patients may not be aware of robust metrics that can help gauge the efficacy of their programs in saving the lives of injured patients. 'traumar' provides robust functions driven by the academic literature to automate the calculation of relevant metrics to individuals desiring to measure the performance of their trauma center or even a trauma system. 'traumar' also provides some helper functions for the data analysis journey. Users can refer to the following publications for descriptions of the methods used in 'traumar'. TRISS methodology, including probability of survival, and the W, M, and Z Scores - Flora (1978) <doi:10.1097/00005373-197810000-00003>, Boyd et al. (1987, PMID:3106646), Llullaku et al. (2009) <doi:10.1186/1749-7922-4-2>, Singh et al. (2011) <doi:10.4103/0974-2700.86626>, Baker et al. (1974, PMID:4814394), and Champion et al. (1989) <doi:10.1097/00005373-198905000-00017>. For the Relative Mortality Metric, see Napoli et al. (2017) <doi:10.1080/24725579.2017.1325948>, Schroeder et al. (2019) <doi:10.1080/10903127.2018.1489021>, and Kassar et al. (2016) <doi:10.1177/00031348221093563>.
Maintained by Nicolas Foss. Last updated 16 days ago.
emsmortalitypiprobabilityqualitysurvivaltraumatriss
5.2 match 3 stars 4.02 score
bart1
move2:Processing and Analysing Animal Trajectories
Tools to handle, manipulate and explore trajectory data, with an emphasis on data from tracked animals. The package is designed to support large studies with several million location records and keep track of units where possible. Data import directly from 'movebank' <https://www.movebank.org/cms/movebank-main> and files is facilitated.
Maintained by Bart Kranstauber. Last updated 1 months ago.
2.8 match 7.51 score 169 scripts 1 dependents
z267xu
ggmulti:High Dimensional Data Visualization
It provides materials (i.e. 'serial axes' objects, Andrew's plot, various glyphs for scatter plot) to visualize high dimensional data.
Maintained by Zehao Xu. Last updated 2 years ago.
3.4 match 6.11 score 36 scripts 4 dependentsbusiness-science
anomalize:Tidy Anomaly Detection
The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.
Maintained by Matt Dancho. Last updated 1 years ago.
anomalyanomaly-detectiondecompositiondetect-anomaliesiqrtime-series
2.2 match 339 stars 9.56 score 332 scripts
apreshill
bakeoff:Data from "The Great British Bake Off"
Data about the bakers, challenges, and ratings for "The Great British Bake Off", from Wikipedia <https://en.wikipedia.org/wiki/The_Great_British_Bake_Off>.
Maintained by Alison Hill. Last updated 2 years ago.
3.6 match 67 stars 5.71 score 77 scripts
kuadrat
growR:Implementation of the Vegetation Model ModVege
Run grass growth simulations using a grass growth model based on ModVege (Jouven, M., P. Carrère, and R. Baumont "Model Predicting Dynamics of Biomass, Structure and Digestibility of Herbage in Managed Permanent Pastures. 1. Model Description." (2006) <doi:10.1111/j.1365-2494.2006.00515.x>). The implementation in this package contains a few additions to the above cited version of ModVege, such as simulations of management decisions, and influences of snow cover. As such, the model is fit to simulate grass growth in mountainous regions, such as the Swiss Alps. The package also contains routines for calibrating the model and helpful tools for analysing model outputs and performance.
Maintained by Kevin Kramer. Last updated 7 months ago.
agronomygrassgrasslandmodellingsimulation-modeling
3.9 match 3 stars 5.28 score 14 scripts
cshs-hydrology
CSHShydRology:Canadian Hydrological Analyses
A collection of user submitted functions to aid in the analysis of hydrological data.
Maintained by Kevin Shook. Last updated 3 years ago.
3.9 match 4 stars 5.26 score 23 scripts
sammorrissette
SC2API:Blizzard SC2 API Wrapper
A wrapper for Blizzard's Starcraft II (a 2010 real-time strategy game) Application Programming Interface (API). All documented API calls are implemented in an easy-to-use and consistent manner.
Maintained by Samuel Morrissette. Last updated 4 years ago.
5.5 match 1 stars 3.70 score 4 scripts
chaoranhu
smam:Statistical Modeling of Animal Movements
Animal movement models including Moving-Resting Process with Embedded Brownian Motion (Yan et al., 2014, <doi:10.1007/s10144-013-0428-8>; Pozdnyakov et al., 2017, <doi:10.1007/s11009-017-9547-6>), Brownian Motion with Measurement Error (Pozdnyakov et al., 2014, <doi:10.1890/13-0532.1>), Moving-Resting-Handling Process with Embedded Brownian Motion (Pozdnyakov et al., 2020, <doi:10.1007/s11009-020-09774-1>), Moving-Resting Process with Measurement Error (Hu et al., 2021, <doi:10.1111/2041-210X.13694>), Moving-Moving Process with two Embedded Brownian Motions.
Maintained by Chaoran Hu. Last updated 1 years ago.
animal-movementbrownian-motionhidden-markov-modelhidden-statesmeasurement-errortelegraph-processgslcpp
4.5 match 3 stars 4.52 score 11 scripts
gallegoj
tfarima:Transfer Function and ARIMA Models
Building customized transfer function and ARIMA models with multiple operators and parameter restrictions. Functions for model identification, model estimation (exact or conditional maximum likelihood), model diagnostic checking, automatic outlier detection, calendar effects, forecasting and seasonal adjustment. See Bell and Hillmer (1983) <doi:10.1080/01621459.1983.10478005>, Box, Jenkins, Reinsel and Ljung <ISBN:978-1-118-67502-1>, Box, Pierce and Newbold (1987) <doi:10.1080/01621459.1987.10478430>, Box and Tiao (1975) <doi:10.1080/01621459.1975.10480264>, Chen and Liu (1993) <doi:10.1080/01621459.1993.10594321>.
Maintained by Jose L. Gallego. Last updated 12 months ago.
5.0 match 2 stars 4.04 score 11 scripts
schochastics
networkdata:Repository of Network Datasets
The package contains a large collection of network dataset with different context. This includes social networks, animal networks and movie networks. All datasets are in 'igraph' format.
Maintained by David Schoch. Last updated 12 months ago.
4.0 match 143 stars 5.01 score 143 scripts
silvaneojunior
kDGLM:Bayesian Analysis of Dynamic Generalized Linear Models
Provide routines for filtering and smoothing, forecasting, sampling and Bayesian analysis of Dynamic Generalized Linear Models using the methodology described in Alves et al. (2024)<doi:10.48550/arXiv.2201.05387> and dos Santos Jr. et al. (2024)<doi:10.48550/arXiv.2403.13069>.
Maintained by Silvaneo Vieira dos Santos Junior. Last updated 4 days ago.
3.5 match 2 stars 5.70 score 9 scripts
r4ss
r4ss:R Code for Stock Synthesis
A collection of R functions for use with Stock Synthesis, a fisheries stock assessment modeling platform written in ADMB by Dr. Richard D. Methot at the NOAA Northwest Fisheries Science Center. The functions include tools for summarizing and plotting results, manipulating files, visualizing model parameterizations, and various other common stock assessment tasks. This version of '{r4ss}' is compatible with Stock Synthesis versions 3.24 through 3.30 (specifically version 3.30.23.1, from December 2024). Support for 3.24 models is only through the core functions for reading output and plotting.
Maintained by Ian G. Taylor. Last updated 5 days ago.
fisheriesfisheries-stock-assessmentstock-synthesis
1.8 match 43 stars 11.38 score 1.0k scripts 2 dependents
ajmcneil
tscopula:Time Series Copula Models
Functions for the analysis of time series using copula models. The package is based on methodology described in the following references. McNeil, A.J. (2021) <doi:10.3390/risks9010014>, Bladt, M., & McNeil, A.J. (2021) <doi:10.1016/j.ecosta.2021.07.004>, Bladt, M., & McNeil, A.J. (2022) <doi:10.1515/demo-2022-0105>.
Maintained by Alexander McNeil. Last updated 25 days ago.
3.6 match 2 stars 5.53 score 12 scriptsconfig-i1
greybox:Toolbox for Model Building and Forecasting
Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Maintained by Ivan Svetunkov. Last updated 3 days ago.
forecastingmodel-selectionmodel-selection-and-evaluationregressionregression-modelsstatisticscpp
1.8 match 30 stars 11.03 score 97 scripts 34 dependents
ykang
gratis:Generating Time Series with Diverse and Controllable Characteristics
Generates synthetic time series based on various univariate time series models including MAR and ARIMA processes. Kang, Y., Hyndman, R.J., Li, F.(2020) <doi:10.1002/sam.11461>.
Maintained by Feng Li. Last updated 11 months ago.
data-generationmixture-autoregressivestatistical-computingtime-series
2.8 match 76 stars 6.98 score 25 scriptsrjdverse
rjd3filters:Trend-Cycle Extraction with Linear Filters based on JDemetra+ v3.x
This package provides functions to build and apply symmetric and asymmetric moving averages (= linear filters) for trend-cycle extraction. In particular, it implements several modern approaches for real-time estimates from the viewpoint of revisions and time delay in detecting turning points. It includes the local polynomial approach of Proietti and Luati (2008), the Reproducing Kernel Hilbert Space (RKHS) of Dagum and Bianconcini (2008) and the Fidelity-Smoothness-Timeliness approach of Grun-Rehomme, Guggemos, and Ladiray (2018). It is based on Java libraries developped in 'JDemetra+' (<https://github.com/jdemetra>), time series analysis software.
Maintained by Alain Quartier-la-Tente. Last updated 15 days ago.
3.8 match 3 stars 5.19 score 77 scripts 3 dependents
yogasatria30
sgstar:Seasonal Generalized Space Time Autoregressive (S-GSTAR) Model
A set of function that implements for seasonal multivariate time series analysis based on Seasonal Generalized Space Time Autoregressive with Seemingly Unrelated Regression (S-GSTAR-SUR) Model by Setiawan(2016)<https://www.researchgate.net/publication/316517889_S-GSTAR-SUR_model_for_seasonal_spatio_temporal_data_forecasting>.
Maintained by M. Yoga Satria Utama Developer. Last updated 4 years ago.
7.2 match 2.70 score 8 scripts
smbc-nzp
MigConnectivity:Estimate Migratory Connectivity for Migratory Animals
Allows the user to estimate transition probabilities for migratory animals between any two phases of the annual cycle, using a variety of different data types. Also quantifies the strength of migratory connectivity (MC), a standardized metric to quantify the extent to which populations co-occur between two phases of the annual cycle. Includes functions to estimate MC and the more traditional metric of migratory connectivity strength (Mantel correlation) incorporating uncertainty from multiple sources of sampling error. For cross-species comparisons, methods are provided to estimate differences in migratory connectivity strength, incorporating uncertainty. See Cohen et al. (2018) <doi:10.1111/2041-210X.12916>, Cohen et al. (2019) <doi:10.1111/ecog.03974>, and Roberts et al. (2023) <doi:10.1002/eap.2788> for details on some of these methods.
Maintained by Jeffrey A. Hostetler. Last updated 12 months ago.
2.8 match 8 stars 6.77 score 41 scripts
mattmar
dynamAedes:A Unified Mechanistic Model for the Population Dynamics of Invasive Aedes Mosquitoes
Generalised model for population dynamics of invasive Aedes mosquitoes. Rationale and model structure are described here: Da Re et al. (2021) <doi:10.1016/j.ecoinf.2020.101180> and Da Re et al. (2022) <doi:10.1101/2021.12.21.473628>.
Maintained by Matteo Marcantonio. Last updated 1 years ago.
ecologyinvasive-speciesmodellingmosquitoespathogens
3.4 match 7 stars 5.59 score 11 scripts
mpiktas
midasr:Mixed Data Sampling Regression
Methods and tools for mixed frequency time series data analysis. Allows estimation, model selection and forecasting for MIDAS regressions.
Maintained by Vaidotas Zemlys-Balevičius. Last updated 3 years ago.
3.3 match 77 stars 5.76 score 150 scripts
mikejohnson51
nwmTools:nwmTools
Tools for working with operational and historic National Water Model Output.
Maintained by Mike Johnson. Last updated 3 months ago.
6.1 match 19 stars 3.06 score 12 scriptspoissonconsulting
dttr2:Manipulate Date, POSIXct and hms Vectors
Manipulates date ('Date'), date time ('POSIXct') and time ('hms') vectors. Date/times are considered discrete and are floored whenever encountered. Times are wrapped and time zones are maintained unless explicitly altered by the user.
Maintained by Ayla Pearson. Last updated 2 months ago.
3.3 match 10 stars 5.65 score 5 scripts 6 dependents
edm44
msdrought:Seasonal Mid-Summer Drought Characteristics
Characterization of a mid-summer drought (MSD) with precipitation based statistics. The MSD is a phenomenon of decreased rainfall during a typical rainy season. It is a feature of rainfall in much of Central America and is also found in other locations, typically those with a Mediterranean climate. Details on the metrics are in Maurer et al. (2022) <doi:10.5194/hess-26-1425-2022>.
Maintained by Ed Maurer. Last updated 9 days ago.
3.5 match 5.30 score 6 scripts
ropensci
tsbox:Class-Agnostic Time Series
Time series toolkit with identical behavior for all time series classes: 'ts','xts', 'data.frame', 'data.table', 'tibble', 'zoo', 'timeSeries', 'tsibble', 'tis' or 'irts'. Also converts reliably between these classes.
Maintained by Christoph Sax. Last updated 5 months ago.
1.8 match 150 stars 10.61 score 496 scripts 4 dependentshzambran
hydroGOF:Goodness-of-Fit Functions for Comparison of Simulated and Observed Hydrological Time Series
S3 functions implementing both statistical and graphical goodness-of-fit measures between observed and simulated values, mainly oriented to be used during the calibration, validation, and application of hydrological models. Missing values in observed and/or simulated values can be removed before computations. Comments / questions / collaboration of any kind are very welcomed.
Maintained by Mauricio Zambrano-Bigiarini. Last updated 10 months ago.
1.8 match 40 stars 10.29 score 796 scripts 8 dependents
frbcesab
forcis:An R Client to Access the FORCIS Database
Provides an interface to the FORCIS database (<https://zenodo.org/doi/10.5281/zenodo.7390791>) on global foraminifera distribution. This package allows to download and to handle FORCIS data. It is part of the FRB-CESAB working group FORCIS. <https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/forcis/>.
Maintained by Nicolas Casajus. Last updated 12 days ago.
3.2 match 4 stars 5.76 score 5 scripts
andreacapozio
TMDb:Access to TMDb API
Provides an R-interface to the TMDb API (see TMDb API on <https://developers.themoviedb.org/3/getting-started/introduction>). The Movie Database (TMDb) is a popular user editable database for movies and TV shows (see <https://www.themoviedb.org>).
Maintained by Andrea Capozio. Last updated 5 years ago.
9.1 match 2.00 score 99 scripts
ecor
RMAWGEN:Multi-Site Auto-Regressive Weather GENerator
S3 and S4 functions are implemented for spatial multi-site stochastic generation of daily time series of temperature and precipitation. These tools make use of Vector AutoRegressive models (VARs). The weather generator model is then saved as an object and is calibrated by daily instrumental "Gaussianized" time series through the 'vars' package tools. Once obtained this model, it can it can be used for weather generations and be adapted to work with several climatic monthly time series.
Maintained by Emanuele Cordano. Last updated 26 days ago.
3.2 match 3 stars 5.62 score 115 scripts 4 dependents
marshalllab
MGDrivE2:Mosquito Gene Drive Explorer 2
A simulation modeling framework which significantly extends capabilities from the 'MGDrivE' simulation package via a new mathematical and computational framework based on stochastic Petri nets. For more information about 'MGDrivE', see our publication: <https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.13318>. Some of the notable capabilities of 'MGDrivE2' include: incorporation of human populations, epidemiological dynamics, time-varying parameters, and a continuous-time simulation framework with various sampling algorithms for both deterministic and stochastic interpretations. 'MGDrivE2' relies on the genetic inheritance structures provided in package 'MGDrivE', so we suggest installing that package initially.
Maintained by Sean L. Wu. Last updated 4 years ago.
2.9 match 6 stars 6.33 score 30 scripts
zivankaraman
CDSE:'Copernicus Data Space Ecosystem' API Wrapper
Provides interface to the 'Copernicus Data Space Ecosystem' API <https://dataspace.copernicus.eu/analyse/apis>, mainly for searching the catalog of available data from Copernicus Sentinel missions and obtaining the images for just the area of interest based on selected spectral bands. The package uses the 'Sentinel Hub' REST API interface <https://dataspace.copernicus.eu/analyse/apis/sentinel-hub> that provides access to various satellite imagery archives. It allows you to access raw satellite data, rendered images, statistical analysis, and other features. This package is in no way officially related to or endorsed by Copernicus.
Maintained by Zivan Karaman. Last updated 1 months ago.
copernicusearth-observationremote-sensing
3.7 match 15 stars 4.91 score 12 scripts
earthsystemdiagnostics
sedproxy:Simulation of Sediment Archived Climate Proxy Records
Proxy forward modelling for sediment archived climate proxies such as Mg/Ca, d18O or Alkenones. The user provides a hypothesised "true" past climate, such as output from a climate model, and details of the sedimentation rate and sampling scheme of a sediment core. Sedproxy returns simulated proxy records. Implements the methods described in Dolman and Laepple (2018) <doi:10.5194/cp-14-1851-2018>.
Maintained by Andrew Dolman. Last updated 1 months ago.
3.5 match 7 stars 5.10 score 18 scripts
airpino
HistDAWass:Histogram-Valued Data Analysis
In the framework of Symbolic Data Analysis, a relatively new approach to the statistical analysis of multi-valued data, we consider histogram-valued data, i.e., data described by univariate histograms. The methods and the basic statistics for histogram-valued data are mainly based on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric between quantile functions. The package contains unsupervised classification techniques, least square regression and tools for histogram-valued data and for histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi: 10.1007/s11634-014-0176-4>.
Maintained by Antonio Irpino. Last updated 1 years ago.
3.8 match 5 stars 4.75 score 75 scriptsasael697
nortsTest:Assessing Normality of Stationary Process
Despite that several tests for normality in stationary processes have been proposed in the literature, consistent implementations of these tests in programming languages are limited. Seven normality test are implemented. The asymptotic Lobato & Velasco's, asymptotic Epps, Psaradakis and Vávra, Lobato & Velasco's and Epps sieve bootstrap approximations, El bouch et al., and the random projections tests for univariate stationary process. Some other diagnostics such as, unit root test for stationarity, seasonal tests for seasonality, and arch effect test for volatility; are also performed. Additionally, the El bouch test performs normality tests for bivariate time series. The package also offers residual diagnostic for linear time series models developed in several packages.
Maintained by Asael Alonzo Matamoros. Last updated 1 years ago.
4.8 match 3 stars 3.69 score 33 scripts
rudeboybert
resampledata:Data Sets for Mathematical Statistics with Resampling in R
Package of data sets from "Mathematical Statistics with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg.
Maintained by Albert Y. Kim. Last updated 4 months ago.
3.4 match 15 stars 5.15 score 187 scripts
georgeweigt
itsmr:Time Series Analysis Using the Innovations Algorithm
Provides functions for modeling and forecasting time series data. Forecasting is based on the innovations algorithm. A description of the innovations algorithm can be found in the textbook "Introduction to Time Series and Forecasting" by Peter J. Brockwell and Richard A. Davis. <https://link.springer.com/book/10.1007/b97391>.
Maintained by George Weigt. Last updated 3 years ago.
7.6 match 2.34 score 218 scriptsrjdverse
rjd3highfreq:Seasonal Adjustment of High Frequency Data with 'JDemetra+ 3.x'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It provides functions for seasonal adjustment of high-frequency data displaying multiple, non integer periodicities. Pre-adjustment with extended airline model and Arima Model Based decomposition.
Maintained by Jean Palate. Last updated 8 months ago.
3.3 match 2 stars 5.15 score 33 scripts 3 dependents
softwareliteracy
rEDM:Empirical Dynamic Modeling ('EDM')
An implementation of 'EDM' algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library. It implements the 'simplex' projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the 'S-map' algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, 'multiview embedding' described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Maintained by Joseph Park. Last updated 11 months ago.
2.8 match 2 stars 6.05 score 319 scripts 1 dependents
daniel-dok
phenex:Auxiliary Functions for Phenological Data Analysis
Provides some easy-to-use functions for spatial analyses of (plant-) phenological data sets and satellite observations of vegetation.
Maintained by Daniel Doktor. Last updated 8 years ago.
7.5 match 2 stars 2.28 score 32 scripts 1 dependentsgeobosh
lagged:Classes and Methods for Lagged Objects
Provides classes and methods for objects, whose indexing naturally starts from zero. Subsetting, indexing and mathematical operations are defined naturally between lagged objects and lagged and base R objects. Recycling is not used, except for singletons. The single bracket operator doesn't drop dimensions by default.
Maintained by Georgi N. Boshnakov. Last updated 3 years ago.
3.7 match 4.64 score 13 scripts 2 dependents
jonasbhend
easyVerification:Ensemble Forecast Verification for Large Data Sets
Set of tools to simplify application of atomic forecast verification metrics for (comparative) verification of ensemble forecasts to large data sets. The forecast metrics are imported from the 'SpecsVerification' package, and additional forecast metrics are provided with this package. Alternatively, new user-defined forecast scores can be implemented using the example scores provided and applied using the functionality of this package.
Maintained by Jonas Bhend. Last updated 2 years ago.
2.8 match 1 stars 6.04 score 61 scripts 4 dependentsaqlt
rjd3report:Quality Assessment and Reportiing for Seasonal Adjustment
Add-in to the 'RJDemetra' package on seasonal adjustments. It allows to produce quality assessments outputs (such as dashboards).
Maintained by Alain Quartier-la-Tente. Last updated 4 months ago.
7.1 match 1 stars 2.30 score 2 scripts
colindouglas
retrosheet:Import Professional Baseball Data from 'Retrosheet'
A collection of tools to import and structure the (currently) single-season event, game-log, roster, and schedule data available from <https://www.retrosheet.org>. In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. This package does the parsing on those files, returning the requested data in the most practical R structure to use for sabermetric or other analyses.
Maintained by Colin Douglas. Last updated 1 years ago.
baseball-analyticsbaseball-databaseball-statisticsgamelogretrosheet
3.9 match 5 stars 4.18 score 30 scripts