Showing 200 of total 482 results (show query)

gshs-ornl

wbstats:Programmatic Access to Data and Statistics from the World Bank API

Search and download data from the World Bank Data API.

Maintained by Jesse Piburn. Last updated 4 years ago.

open-dataworld-bankworld-bank-apiworldbank

50.1 match 126 stars 10.06 score 1.1k scripts 3 dependents

adeckmyn

maps:Draw Geographical Maps

Display of maps. Projection code and larger maps are in separate packages ('mapproj' and 'mapdata').

Maintained by Alex Deckmyn. Last updated 2 months ago.

15.1 match 24 stars 14.70 score 19k scripts 490 dependents

ropensci

rnaturalearth:World Map Data from Natural Earth

Facilitates mapping by making natural earth map data from <https://www.naturalearthdata.com/> more easily available to R users.

Maintained by Philippe Massicotte. Last updated 1 days ago.

peer-reviewed

11.8 match 234 stars 15.51 score 7.2k scripts 47 dependents

andysouth

rworldmap:Mapping Global Data

Enables mapping of country level and gridded user datasets.

Maintained by Andy South. Last updated 2 years ago.

15.1 match 30 stars 11.83 score 3.2k scripts 14 dependents

dnychka

fields:Tools for Spatial Data

For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get started and for an overview. The fields source code is deliberately commented and provides useful explanations of numerical details as a companion to the manual pages. The commented source code can be viewed by expanding the source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857, the National Center for Atmospheric Research, and Colorado School of Mines. See the Fields URL for a vignette on using this package and some background on spatial statistics.

Maintained by Douglas Nychka. Last updated 9 months ago.

fortran

10.1 match 15 stars 12.60 score 7.7k scripts 295 dependents

predictiveecology

NetLogoR:Build and Run Spatially Explicit Agent-Based Models

Build and run spatially explicit agent-based models using only the R platform. 'NetLogoR' follows the same framework as the 'NetLogo' software (Wilensky (1999) <http://ccl.northwestern.edu/netlogo/>) and is a translation in R of the structure and functions of 'NetLogo'. 'NetLogoR' provides new R classes to define model agents and functions to implement spatially explicit agent-based models in the R environment. This package allows benefiting of the fast and easy coding phase from the highly developed 'NetLogo' framework, coupled with the versatility, power and massive resources of the R software. Examples of two models from the NetLogo software repository (Ants <http://ccl.northwestern.edu/netlogo/models/Ants>) and Wolf-Sheep-Predation (<http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation>), and a third, Butterfly, from Railsback and Grimm (2012) <https://www.railsback-grimm-abm-book.com/>, all written using 'NetLogoR' are available. The 'NetLogo' code of the original version of these models is provided alongside. A programming guide inspired from the 'NetLogo' Programming Guide (<https://ccl.northwestern.edu/netlogo/docs/programming.html>) and a dictionary of 'NetLogo' primitives (<https://ccl.northwestern.edu/netlogo/docs/dictionary.html>) equivalences are also available. NOTE: To increment 'time', these functions can use a for loop or can be integrated with a discrete event simulator, such as 'SpaDES' (<https://cran.r-project.org/package=SpaDES>). The suggested package 'fastshp' can be installed with 'install.packages("fastshp", repos = ("<https://rforge.net>"), type = "source")'.

Maintained by Eliot J B McIntire. Last updated 4 months ago.

16.3 match 38 stars 6.94 score 19 scripts

pik-piam

mrremind:MadRat REMIND Input Data Package

The mrremind packages contains data preprocessing for the REMIND model.

Maintained by Lavinia Baumstark. Last updated 9 hours ago.

17.2 match 4 stars 6.26 score 15 scripts 1 dependents

rspatial

geosphere:Spherical Trigonometry

Spherical trigonometry for geographic applications. That is, compute distances and related measures for angular (longitude/latitude) locations.

Maintained by Robert J. Hijmans. Last updated 6 months ago.

cpp

6.8 match 36 stars 13.79 score 5.7k scripts 116 dependents

dankelley

ocedata:Oceanographic Data Sets for 'oce' Package

Several Oceanographic data sets are provided for use by the 'oce' package, and for other purposes.

Maintained by Dan Kelley. Last updated 2 years ago.

14.2 match 8 stars 5.07 score 146 scripts

bodkan

slendr:A Simulation Framework for Spatiotemporal Population Genetics

A framework for simulating spatially explicit genomic data which leverages real cartographic information for programmatic and visual encoding of spatiotemporal population dynamics on real geographic landscapes. Population genetic models are then automatically executed by the 'SLiM' software by Haller et al. (2019) <doi:10.1093/molbev/msy228> behind the scenes, using a custom built-in simulation 'SLiM' script. Additionally, fully abstract spatial models not tied to a specific geographic location are supported, and users can also simulate data from standard, non-spatial, random-mating models. These can be simulated either with the 'SLiM' built-in back-end script, or using an efficient coalescent population genetics simulator 'msprime' by Baumdicker et al. (2022) <doi:10.1093/genetics/iyab229> with a custom-built 'Python' script bundled with the R package. Simulated genomic data is saved in a tree-sequence format and can be loaded, manipulated, and summarised using tree-sequence functionality via an R interface to the 'Python' module 'tskit' by Kelleher et al. (2019) <doi:10.1038/s41588-019-0483-y>. Complete model configuration, simulation and analysis pipelines can be therefore constructed without a need to leave the R environment, eliminating friction between disparate tools for population genetic simulations and data analysis.

Maintained by Martin Petr. Last updated 13 days ago.

popgenpopulation-geneticssimulationsspatial-statistics

6.3 match 56 stars 9.15 score 88 scripts

andrewzm

FRK:Fixed Rank Kriging

A tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of basis functions. This fixed-rank basis-function representation facilitates the modelling of big data, and the method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above also supports the modelling of non-Gaussian data (e.g., Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian) by employing a generalised linear mixed model (GLMM) framework. Zammit-Mangion and Cressie <doi:10.18637/jss.v098.i04> describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs, while Sainsbury-Dale, Zammit-Mangion, and Cressie <doi:10.18637/jss.v108.i10> describe `FRK` in a non-Gaussian setting; two vignettes are available that summarise these papers and provide additional examples.

Maintained by Andrew Zammit-Mangion. Last updated 6 months ago.

cpp

6.3 match 71 stars 8.70 score 188 scripts 1 dependents

nenuial

geographer:Geography Vizualisations

Provides function and objects to establish vizualisations for my Geography lessons.

Maintained by Pascal Burkhard. Last updated 24 days ago.

16.9 match 1 stars 2.78 score

pik-piam

luplot:Landuse Plot Library

Some useful functions to plot data such as a map plot function for MAgPIE objects.

Maintained by Benjamin Bodirsky. Last updated 2 months ago.

7.6 match 6.16 score 124 scripts 11 dependents

wch

gcookbook:Data for "R Graphics Cookbook"

Data sets used in the book "R Graphics Cookbook" by Winston Chang, published by O'Reilly Media.

Maintained by Winston Chang. Last updated 6 years ago.

6.7 match 10 stars 6.77 score 1.3k scripts 1 dependents

wilkox

treemapify:Draw Treemaps in 'ggplot2'

Provides 'ggplot2' geoms for drawing treemaps.

Maintained by David Wilkins. Last updated 9 months ago.

data-visualisationggplot2treemap

3.4 match 215 stars 12.58 score 1.6k scripts 9 dependents

mthrun

DataVisualizations:Visualizations of High-Dimensional Data

Gives access to data visualisation methods that are relevant from the data scientist's point of view. The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) for either classified or non-classified multivariate data published in Thrun, M.C. et al.: "Analyzing the Fine Structure of Distributions" (2020), PLoS ONE, <DOI:10.1371/journal.pone.0238835>. The MD-plot outperforms the box-and-whisker diagram (box plot), violin plot and bean plot and geom_violin plot of ggplot2. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.

Maintained by Michael Thrun. Last updated 2 months ago.

cpp

5.4 match 7 stars 7.72 score 118 scripts 7 dependents

dmurdoch

plotrix:Various Plotting Functions

Lots of plots, various labeling, axis and color scaling functions. The author/maintainer died in September 2023.

Maintained by Duncan Murdoch. Last updated 1 years ago.

3.6 match 5 stars 11.31 score 9.2k scripts 361 dependents

colearendt

tidyjson:Tidy Complex 'JSON'

Turn complex 'JSON' data into tidy data frames.

Maintained by Cole Arendt. Last updated 2 years ago.

3.8 match 192 stars 10.64 score 522 scripts 7 dependents

coolbutuseless

tickle:Easily Build Tcl/Tk UIs

Wrap tcltk to make GUI creation easier.

Maintained by mikefc. Last updated 3 years ago.

6.5 match 125 stars 5.88 score 11 scripts

thiyangt

denguedatahub:A Tidy Format Datasets of Dengue by Country

Provides a weekly, monthly, yearly summary of dengue cases by state/ province/ country.

Maintained by Thiyanga S. Talagala. Last updated 1 months ago.

openjdk

7.0 match 11 stars 5.12 score 34 scripts

trinker

wakefield:Generate Random Data Sets

Generates random data sets including: data.frames, lists, and vectors.

Maintained by Tyler Rinker. Last updated 5 years ago.

data-generationwakefield

4.5 match 256 stars 7.13 score 209 scripts

alanarnholt

BSDA:Basic Statistics and Data Analysis

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

Maintained by Alan T. Arnholt. Last updated 2 years ago.

3.3 match 7 stars 9.11 score 1.3k scripts 6 dependents

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

3.5 match 302 stars 7.63 score 89 scripts

arilamstein

choroplethrMaps:Contains Maps Used by the 'choroplethr' Package

Contains 3 maps. 1) US States 2) US Counties 3) Countries of the world.

Maintained by Ari Lamstein. Last updated 7 years ago.

5.0 match 4.80 score 418 scripts 1 dependents

andysouth

rworldxtra:Country boundaries at high resolution.

High resolution vector country boundaries derived from Natural Earth data, can be plotted in rworldmap.

Maintained by Andy South. Last updated 10 years ago.

3.3 match 4 stars 6.75 score 338 scripts 4 dependents

reconverse

outbreaks:A Collection of Disease Outbreak Data

Empirical or simulated disease outbreak data, provided either as RData or as text files.

Maintained by Finlay Campbell. Last updated 2 years ago.

3.3 match 51 stars 6.70 score 282 scripts

carloscinelli

benford.analysis:Benford Analysis for Data Validation and Forensic Analytics

Provides tools that make it easier to validate data using Benford's Law.

Maintained by Carlos Cinelli. Last updated 6 years ago.

3.8 match 62 stars 5.66 score 74 scripts

sammo3182

drhur:Learning R with Dr. Hu

Tutarials of R learning easily and happily.

Maintained by Yue Hu. Last updated 1 years ago.

3.4 match 18 stars 6.06 score 16 scripts

jlacko

RCzechia:Spatial Objects of the Czech Republic

Administrative regions and other spatial objects of the Czech Republic.

Maintained by Jindra Lacko. Last updated 3 days ago.

czech-republicshapefile

3.0 match 25 stars 6.87 score 85 scripts

jvanschalkwyk

corona:Coronavirus ('Rona') Data Exploration

Manipulate and view coronavirus data and other societally relevant data at a basic level.

Maintained by Jo van Schalkwyk. Last updated 4 years ago.

7.1 match 2.70 score 1 scripts

pik-piam

mrindustry:input data generation for the REMIND industry module

The mrindustry packages contains data preprocessing for the REMIND model.

Maintained by Falk Benke. Last updated 9 hours ago.

3.5 match 5.43 score 2 dependents

alanarnholt

PASWR:Probability and Statistics with R

Functions and data sets for the text Probability and Statistics with R.

Maintained by Alan T. Arnholt. Last updated 3 years ago.

4.0 match 2 stars 4.70 score 241 scripts

hanase

wpp2019:World Population Prospects 2019

Provides data from the United Nation's World Population Prospects 2019.

Maintained by Hana Sevcikova. Last updated 5 years ago.

5.6 match 1 stars 3.17 score 99 scripts 5 dependents

frbcesab

rutils:A Collection of R Functions

A collection of R functions commonly used in FRB-CESAB projects.

Maintained by Nicolas Casajus. Last updated 2 months ago.

miscellaneous

3.7 match 2 stars 4.66 score 454 scripts

alanarnholt

PASWR2:Probability and Statistics with R, Second Edition

Functions and data sets for the text Probability and Statistics with R, Second Edition.

Maintained by Alan T. Arnholt. Last updated 3 years ago.

4.0 match 1 stars 4.24 score 260 scripts