Applied Statistics

R Packages

R package PRSim

Provides a simulation framework to simulate streamflow time series with similar main characteristics as observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. The approach is based on the randomization of the phases of the Fourier transform. We further use the flexible four-parameter Kappa distribution, which allows for the extrapolation to yet unobserved low and high flows.

A stable version of the package is posted on CRAN, a development version is posted here.

R package varrank

varrank: Heuristics Tools Based on Mutual Information for Variable Ranking. A computational toolbox of heuristics approaches for performing variable ranking and feature selection based on mutual information well adapted for multivariate system epidemiology datasets. The core function is a general implementation of the minimum redundancy maximum relevance model. Variables ranking can be learned with a sequential forward/backward search algorithm. The two main problems that can be addressed by this package is the selection of the most representative variable within a group of variables of interest (i.e. dimension reduction) and variable ranking with respect to a set of features of interest.

Webpage (based on pkgdown); a stable version of the package is posted on CRAN.

R package spam

spam: an R package, a collection of functions based in R/Fortran for sparse matrix algebra, tailored for MCMC calculations within GMRF or GRF with compactly supported covariance functions. Emphasis is given on a comprehensive, simple, tutorial structure of the code. 

Webpage (based on pkgdown); a stable version of the package is posted on CRAN, a development version is posted here.

R package mcmcabn

mcmcabn: Flexible implementation of a structural MCMC sampler for Directed Acyclic Graphs (DAGs). It supports new edge reversal move and the Markov blanket resampling from as well as three priors: a prior controlling for structure complexity, an uninformative prior and a user defined prior. The three main problems that can be addressed by this R package are selecting the most probable structure based on a cache of pre-computed scores, controlling for overfitting and sampling the landscape of high scoring structures.

Webpage (based on pkgdown); a stable version of the package is posted on CRAN, a development version is posted here.

R package abn

abn: An R package to providing routines to help determine optimal Bayesian network models for a given data set, where these models are used to identify statistical dependencies in messy, complex data.

Webpage http://r-bayesian-networks.org.  A stable version of the package is posted on CRAN

R package tsabn

tsabn is an R package that extends the abn R package for time series analysis. This is a machine learning approach to empirically identifying associations in complex and high dimensional datasets of time series.

A current version of the package is available here.

R package varycoef

The R package provides ML method to estimate and predict Spatially Varying Coefficient (SVC) Models. It supports covariance tapering by Furrer et al. (2006) to support ML estimation on large data.

A stable version of the package is available here.

R package spam64

spam64: 64-Bit Extension of the SPArse Matrix R Package 'spam' Provides the Fortran code of the R package 'spam' with 64-bit integers. Loading this package together with the R package 'spam' enables the sparse matrix class "spam" to handle huge sparse matrices with more than 2^31-1 non-zero elements.

A stable version of the package is posted on CRAN, a development version is posted here.

R package dotCall64

dotCall64: Enhanced Foreign Function Interface Supporting Long Vectors.
An alternative version of .C() and .Fortran() supporting long vectors and 64-bit integer type arguments. The provided interface .C64() features mechanisms the avoid unnecessary copies of read-only or write-only arguments. This makes it a convenient and fast interface to C/C++ and Fortran code.

A stable version of the package is posted on CRAN, a development version is posted here.

R package variosig

variosig: Applying Monte Carlo permutation to generate pointwise variogram envelope and checking for spatial dependence at different scales using permutation test. Empirical Brown's method and Fisher's method are used to compute overall p-value for hypothesis test.

A stable version of the package is posted on CRAN.

R package optimParallel

optimParallel: an R package, that provides parallel versions of the gradient-based optim() methods. The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time.

A stable version of the package is posted on CRAN, a development version is posted here.

R package gapfill

gapfill: Fill Missing Values in Satellite Data A R package Tools to fill missing values in satellite data and to develop new gap-fill algorithms. The methods are tailored to data (images) observed at equally-spaced points in time. The package is illustrated with MODIS NDVI data.abn:

A stable version of the package is posted on CRAN.

R package eggCounts

eggCounts: An R package to assess anthelmintic efficacy using Bayesian hierarchical models for faecal egg count data. We have implemented a new Bayesian inference approach through Stan MCMC sampling scheme. Notice that older version did have some issues with the unpaired setting.
 

A stable version of the package is posted on CRAN.

R package rmbsizerR

mrbsizeR: An R package for the multiresolution analysis of spatial fields and images to capture scale-dependent features. mrbsizeR is based on scale space smoothing and uses differences of smooths at neighbouring scales for finding features on different scales. To infer which of the captured features are credible, Bayesian analysis is used.  The method has first been proposed by Holmstrom, Pasanen, Furrer, Sain (2011) <doi:10.1016/j.csda.2011.04.011>.

A stable version of the package is posted on CRAN

R package gsbDesign

gsbDesign: An R package to evaluate group sequential operating characteristics for clinical, Bayesian two-arm trials with known Sigma and normal endpoints.

A stable version of the package is posted on CRAN.

R package fields

fields: Tools for Spatial Data for curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. 

A stable version of the package is posted on CRAN.

R package RandomFieldsUtils

RandomFieldsUtils: Various utilities are provided that might be used in spatial statistics and elsewhere. It delivers a method for solving linear equations that checks the sparsity of the matrix before any algorithm is used. Furthermore, it includes the Struve functions.