Implementation of a statistical approach for estimating the joint health effects of multiple concurrent exposures, as described in Bobb et al (2015) <doi:10.1093/biostatistics/kxu058>.

Computation of asymptotic confidence intervals for negative and positive predictive values in binary diagnostic tests in case-control studies. Experimental design for hypothesis tests on predictive values.

Support ecological analyses such as ordination and clustering. Contains consistent and easy wrapper functions of stat', vegan', and labdsv packages, and visualisation functions of ordination and clustering.

This package provides utilities to facilitate handling of Fude Polygon data downloadable from the Ministry of Agriculture, Forestry and Fisheries website <https://open.fude.maff.go.jp>.

Generalized Mann-Whitney type tests based on probabilistic indices and new diagnostic plots, for the underlying manuscript see Fischer, Oja (2015) <doi:10.18637/jss.v065.i09>.

Fitting and validation of machine learning algorithms for volume prediction of trees, currently for conifer trees based on diameter at breast height and height as explanatory variables.

Detect outlying observations in functional data sets based on the minimum regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam et al. (2023) <arXiv:2307.13509>.

This package performs Multiple Factor Analysis method for quantitative, categorical, frequency and mixed data, in addition to generating a lot of graphics, also has other useful functions.

Mapping Averaged Pairwise Information (MAPI) is an exploratory method providing graphical representations summarizing the spatial variation of pairwise metrics (eg. distance, similarity coefficient, ...) computed between georeferenced samples.

This package provides some functions to get Korean text sample from news articles in Naver which is popular news portal service <https://news.naver.com/> in Korea.

This package provides routines for finding an Optimal System of Distinct Representatives (OSDR), as defined by D.Gale (1968) <doi:10.1016/S0021-9800(68)80039-0>.

Computes the All-Resolution Inference method in the permutation framework, i.e., simultaneous lower confidence bounds for the number of true discoveries. <doi:10.1002/sim.9725>.

Analysis of terms in linear, generalized and mixed linear models, on the basis of multiple comparisons of factor contrasts. Specially suited for the analysis of interaction terms.

It's a Super K-Nearest Neighbor classification method with using kernel density to describe weight of the distance between a training observation and the testing sample.

Access Amazon Web Service Simple Storage Service ('S3') <https://aws.amazon.com/s3/> as if it were a file system. Interface based on the R package fs'.

Independent Surrogate Variable Analysis is an algorithm for feature selection in the presence of potential confounding factors (see Teschendorff AE et al 2011, <doi: 10.1093/bioinformatics/btr171>).

Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method.

This package implements both real-valued branches of the Lambert-W function (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for installing the entire GSL.

Facilities for working with Atlantis box-geometry model (BGM) files. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model. Functions are provided to read from BGM files directly, preserving their internal topology, as well as helper functions to generate spatial data from these mesh forms. This functionality aims to simplify the creation and modification of box and geometry as well as the ability to integrate with other data sources.

Efficient algorithms for generating ensembles of robust, sparse and diverse models via robust multi-model subset selection (RMSS). The robust ensembles are generated by minimizing the sum of the least trimmed square loss of the models in the ensembles under constraints for the size of the models and the sharing of the predictors. Tuning parameters for the robustness, sparsity and diversity of the robust ensemble are selected by cross-validation.

Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors. Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors.

This package provides analytical methods for analyzing CRISPR screen data at different levels of gene expression. Multi-component normal mixture models and EM algorithms are used for modeling.

This package provides functions to check whether a vector of p-values respects the assumptions of FDR (false discovery rate) control procedures and to compute adjusted p-values.

This package implements the Cross-contribution Compensating Multiple standard Normalization (CCMN) method described in Redestig et al. (2009) Analytical Chemistry <doi:10.1021/ac901143w> and other normalization algorithms.