R-universe search: nuts

ropensci

nuts:Convert European Regional Data

Motivated by changing administrative boundaries over time, the 'nuts' package can convert European regional data with NUTS codes between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam (1983) <doi:10.1559/152304083783914958> based on granular (100m x 100m) area, population and land use data provided by the European Commission's Joint Research Center.

Maintained by Moritz Hennicke. Last updated 5 months ago.

europe european-union eurostat nomenclature nuts nuts-codes nuts-regions regional-data

114.3 match 8 stars 5.86 score 3 scripts

ropengov

regions:Processing Regional Statistics

Validating sub-national statistical typologies, re-coding across standard typologies of sub-national statistics, and making valid aggregate level imputation, re-aggregation, re-weighting and projection down to lower hierarchical levels to create meaningful data panels and time series.

Maintained by Daniel Antal. Last updated 2 years ago.

observatory regions ropengov statistics

30.3 match 12 stars 8.81 score 67 scripts 5 dependents

ropengov

giscoR:Download Map Data from GISCO API - Eurostat

Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.

Maintained by Diego Hernangómez. Last updated 30 days ago.

ropengov spatial api-wrapper eurostat gisco thematic-maps eurostat-data ggplot2 gis

5.7 match 75 stars 10.70 score 424 scripts 5 dependents

ropenspain

mapSpain:Administrative Boundaries of Spain

Administrative Boundaries of Spain at several levels (Autonomous Communities, Provinces, Municipalities) based on the 'GISCO' 'Eurostat' database <https://ec.europa.eu/eurostat/web/gisco> and 'CartoBase SIANE' from 'Instituto Geografico Nacional' <https://www.ign.es/>. It also provides a 'leaflet' plugin and the ability of downloading and processing static tiles.

Maintained by Diego Hernangómez. Last updated 1 months ago.

ropenspain tiles maps spatial municipalities spain gisco provinces ign administrative-boundaries ccaa static-tiles ggplot2 gis

5.3 match 42 stars 8.83 score 244 scripts 2 dependents

paul-buerkner

brms:Bayesian Regression Models using 'Stan'

Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

Maintained by Paul-Christian Bürkner. Last updated 3 days ago.

bayesian-inference brms multilevel-models stan statistical-models

1.8 match 1.3k stars 16.61 score 13k scripts 34 dependents

stan-dev

bayesplot:Plotting for Bayesian Models

Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.

Maintained by Jonah Gabry. Last updated 1 months ago.

bayesian ggplot2 mcmc pandoc stan statistical-graphics visualization

1.8 match 436 stars 16.69 score 6.5k scripts 98 dependents

jschoeley

tricolore:A Flexible Color Scale for Ternary Compositions

Compositional data consisting of three-parts can be color mapped with a ternary color scale. Such a scale is provided by the tricolore packages with options for discrete and continuous colors, mean-centering and scaling. See Jonas Schöley (2021) "The centered ternary balance scheme. A technique to visualize surfaces of unbalanced three-part compositions" <doi:10.4054/DemRes.2021.44.19>, Jonas Schöley, Frans Willekens (2017) "Visualizing compositional data on the Lexis surface" <doi:10.4054/DemRes.2017.36.21>, and Ilya Kashnitsky, Jonas Schöley (2018) "Regional population structures at a glance" <doi:10.1016/S0140-6736(18)31194-2>.

Maintained by Jonas Schöley. Last updated 10 months ago.

3.4 match 151 stars 7.11 score 85 scripts

cole-monnahan-noaa

adnuts:No-U-Turn MCMC Sampling for 'ADMB' Models

Bayesian inference using the no-U-turn (NUTS) algorithm by Hoffman and Gelman (2014) <https://www.jmlr.org/papers/v15/hoffman14a.html>. Designed for 'AD Model Builder' ('ADMB') models, or when R functions for log-density and log-density gradient are available, such as 'Template Model Builder' models and other special cases. Functionality is similar to 'Stan', and the 'rstan' and 'shinystan' packages are used for diagnostics and inference.

Maintained by Cole Monnahan. Last updated 1 years ago.

3.7 match 24 stars 6.33 score 59 scripts

staffanbetner

rethinking:Statistical Rethinking book package

Utilities for fitting and comparing models

Maintained by Richard McElreath. Last updated 3 months ago.

3.8 match 5.42 score 4.4k scripts

giocomai

latlon2map:Facilitates matching lat/lon data with administrative units and other geographic shapes

Facilitates matching lat/lon data with administrative units and other geographic shapes

Maintained by Giorgio Comai. Last updated 5 months ago.

rspatial shiny

5.1 match 10 stars 3.70 score

cotima

CoTiMA:Continuous Time Meta-Analysis ('CoTiMA')

The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from studies that used different time intervals. Different time intervals between measurement occasions impose problems for meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical model comparisons and significance tests are then performed on the continuous time parameter estimates. 'CoTiMA' also allows analysis of publication bias (Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of statistical power (post hoc power, required sample sizes). See Dormann, C., Guthier, C., & Cortina, J. M. (2019) <doi:10.1177/1094428119847277>. and Guthier, C., Dormann, C., & Voelkle, M. C. (2020) <doi:10.1037/bul0000304>.

Maintained by Markus Homberg. Last updated 2 months ago.

3.3 match 4 stars 5.28 score

cran

COUNT:Functions, Data and Code for Count Data

Functions, data and code for Hilbe, J.M. 2011. Negative Binomial Regression, 2nd Edition (Cambridge University Press) and Hilbe, J.M. 2014. Modeling Count Data (Cambridge University Press).

Maintained by Andrew Robinson. Last updated 8 years ago.

6.0 match 2.64 score 1 dependents

epiforecasts

epinowcast:Flexible Hierarchical Nowcasting

Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.

Maintained by Sam Abbott. Last updated 11 months ago.

cmdstanr effective-reproduction-number-estimation epidemiology infectious-disease-surveillance nowcasting outbreak-analysis pandemic-preparedness real-time-infectious-disease-modelling stan

1.8 match 61 stars 7.88 score 65 scripts

epinowcast

epinowcast:Flexible Hierarchical Nowcasting

Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.

Maintained by Sam Abbott. Last updated 11 months ago.

cmdstanr effective-reproduction-number-estimation epidemiology infectious-disease-surveillance nowcasting outbreak-analysis pandemic-preparedness real-time-infectious-disease-modelling stan

1.8 match 61 stars 7.79 score 71 scripts

cran

qPRAentry:Quantitative Pest Risk Assessment at the Entry Step

Supports risk assessors in performing the entry step of the quantitative Pest Risk Assessment. It allows the estimation of the amount of a plant pest entering a risk assessment area (in terms of founder populations) through the calculation of the imported commodities that could be potential pathways of pest entry, and the development of a pathway model. Two 'Shiny' apps based on the functionalities of the package are included, that simplify the process of assessing the risk of entry of plant pests. The approach is based on the work of the European Food Safety Authority (EFSA PLH Panel et al., 2018) <doi:10.2903/j.efsa.2018.5350>.

Maintained by Martina Cendoya. Last updated 3 months ago.

4.9 match 2.70 score

lcef97

SchoolDataIT:Retrieve, Harmonise and Map Open Data Regarding the Italian School System

Compiles and displays the available data sets regarding the Italian school system, with a focus on the infrastructural aspects. Input datasets are downloaded from the web, with the aim of updating everything to real time. The functions are divided in four main modules, namely 'Get', to scrape raw data from the web 'Util', various utilities needed to process raw data 'Group', to aggregate data at the municipality or province level 'Map', to visualize the output datasets.

Maintained by Leonardo Cefalo. Last updated 2 months ago.

3.4 match 3.88 score

danielturek

nimbleHMC:Hamiltonian Monte Carlo and Other Gradient-Based MCMC Sampling Algorithms for 'nimble'

Provides gradient-based MCMC sampling algorithms for use with the MCMC engine provided by the 'nimble' package. This includes two versions of Hamiltonian Monte Carlo (HMC) No-U-Turn (NUTS) sampling, and (under development) Langevin samplers. The `NUTS_classic` sampler implements the original HMC-NUTS algorithm as described in Hoffman and Gelman (2014) <doi:10.48550/arXiv.1111.4246>. The `NUTS` sampler is a modern version of HMC-NUTS sampling matching the HMC sampler available in version 2.32.2 of Stan (Stan Development Team, 2023). In addition, convenience functions are provided for generating and modifying MCMC configuration objects which employ HMC sampling.

Maintained by Daniel Turek. Last updated 3 months ago.

6.2 match 1.79 score 31 scripts

statisticspoland

bdl:Interface and Tools for 'BDL' API

Interface to Local Data Bank ('Bank Danych Lokalnych' - 'bdl') API <https://api.stat.gov.pl/Home/BdlApi?lang=en> with set of useful tools like quick plotting and map generating using data from bank.

Maintained by Krzysztof Kania. Last updated 2 years ago.

1.9 match 20 stars 5.74 score 11 scripts

cran

CAOP.RAA.2024:Official Administrative Map of the Azores (CAOP 2024)

Provides the official administrative boundaries of the Azores (Região Autónoma dos Açores (RAA)) as defined in the 2024 edition of the Carta Administrativa Oficial de Portugal (CAOP), published by the Direção-Geral do Território (DGT). The package includes convenience functions to import these boundaries as 'sf' objects for spatial analysis in R. Source: <https://geo2.dgterritorio.gov.pt/caop/CAOP_RAA_2024-gpkg.zip>.

Maintained by Ramiro Magno. Last updated 3 days ago.

5.3 match 1.70 score

richardli

surveyPrev:Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas

Provides a pipeline to perform small area estimation and prevalence mapping of binary indicators using health and demographic survey data, described in Fuglstad et al. (2022) <doi:10.48550/arXiv.2110.09576> and Wakefield et al. (2020) <doi:10.1111/insr.12400>.

Maintained by Qianyu Dong. Last updated 5 days ago.

1.5 match 1 stars 5.76 score 11 scripts

e-kotov

mapineqr:Access Mapineq Inequality Indicators via API

Access Mapineq inequality indicators via API.

Maintained by Egor Kotov. Last updated 18 days ago.

data demogrpahy socio-economic-indicators

3.5 match 1 stars 2.30 score 3 scripts

cran

qape:Quantile of Absolute Prediction Errors

Estimates QAPE using bootstrap procedures. The residual, parametric and double bootstrap is used. The test of normality using Cholesky decomposition is added. Y pop is defined.

Maintained by Alicja Wolny-Dominiak. Last updated 2 years ago.

6.8 match 1.00 score

thomaswielandgeo

C19dNUTS:Dataset of Regional COVID-19 Deaths per 100,000 Pop (NUTS)

Dataset containing cumulative COVID-19 deaths (absolute and per 100,000 pop) at the regional level (mostly NUTS 3) for 31 EU/EFTA countries.

Maintained by Thomas Wieland. Last updated 2 years ago.

4.9 match 1.00 score

cajoterbraak

PRC:Principal Response Curves (PRC) For Displaying Multivariate Main Effects And Interactions

PRC is a small \code{vegan}-based package to create and display Principal Response Curves (PRC), which are a special case of Redundancy Analysis (rda) for multivariate responses in designed experiments and repeated measurement designs. PRC expresses ordination scores as deviation from a reference, usually to visualize multivariate A-dependent effects (e.g time-dependent effects) of a treatment B in (un)balanced factorial experiments. The main user functions are \code{\link{doPRC}}, \code{\link{plotPRC}} and \code{\link{plotPRC2d}}. The easiest example is the code demo \code{PRC_pyrifos}.

Maintained by Cajo J.F. ter Braak. Last updated 1 years ago.

1.6 match 1.74 score 11 scripts

paolomaranzano

EEAaq:Handle Air Quality Data from the European Environment Agency Data Portal

This software downloads and manages air quality data from the European Environmental Agency (EEA) dataflow (<https://www.eea.europa.eu/data-and-maps/data/aqereporting-9>). See the web page <https://eeadmz1-downloads-webapp.azurewebsites.net/> for details on the EEA's Air Quality Download Service. The package allows dynamically mapping the stations, summarising and time aggregating the measurements and building spatial interpolation maps. See the web page <https://www.eea.europa.eu/en> for further information on EEA activities and history. Further details, as well as, an extended vignette of the main functions included in the package, are available at the GitHub web page dedicated to the project.

Maintained by Paolo Maranzano. Last updated 1 months ago.

2.3 match 1.00 score

corradolanera

depigner:A Utility Package to Help you Deal with "Pignas"

Pigna [_pìn'n'a_] is the Italian word for pine cone. In jargon, it is used to identify a task which is boring, banal, annoying, painful, frustrating and maybe even with a not so beautiful or rewarding result, just like the obstinate act of trying to challenge yourself in extracting pine nuts from a pine cone, provided that, in the end, you will find at least one inside it. Here you can find a backpack of functions to be used to solve small everyday problems of coding or analyzing (clinical) data, which would be normally solved using quick-and-dirty patches. You will be able to convert 'Hmisc' and 'rms' summary()es into data.frames ready to be rendered by 'pander' and 'knitr'. You can access easy-to-use wrappers to activate essential but useful progress bars (from 'progress') into your loops or functionals. Easy setup and control Telegram's bots (from 'telegram.bot') to send messages or to divert error messages to a Telegram's chat. You also have some utilities helping you in the development of packages, like the activation of the same user interface of 'usethis' into your package, or call polite functions to ask a user to install other packages. Finally, you find a set of thematic sets of packages you may use to set up new environments quickly, installing them in a single call.

Maintained by Corrado Lanera. Last updated 2 years ago.

hmisc pigne rms telegram

0.5 match 3 stars 4.14 score 93 scripts

bioc

BASiCStan:Stan implementation of BASiCS

Provides an interface to infer the parameters of BASiCS using the variational inference (ADVI), Markov chain Monte Carlo (NUTS), and maximum a posteriori (BFGS) inference engines in the Stan programming language. BASiCS is a Bayesian hierarchical model that uses an adaptive Metropolis within Gibbs sampling scheme. Alternative inference methods provided by Stan may be preferable in some situations, for example for particularly large data or posterior distributions with difficult geometries.

Maintained by Alan OCallaghan. Last updated 5 months ago.

immunooncology normalization sequencing rnaseq software geneexpression transcriptomics singlecell differentialexpression bayesian cellbiology single-cell-rna-seq cpp

0.5 match 3.78 score 1 scripts

matt-dray

ActionSquirrel:Play An R6-Class 'Action Squirrel' Game

Prints to the console a grid of emoji representing a forest, including a player-controlled squirrel that can be moved by the user to collect nuts and avoid an owl enemy. Collect enough nuts to survive winter.

Maintained by Matt Dray. Last updated 3 years ago.

r6 sonify

0.8 match 3 stars 2.18 score 3 scripts