Hansen's (1995) Covariate-Augmented Dickey-Fuller (CADF) test. The only required argument is y, the Tx1 time series to be tested. If no stationary covariate X is passed to the procedure, then an ordinary ADF test is performed. The p-values of the test are computed using the procedure illustrated in Lupi (2009).

Cellular cooperation compromises the plating efficiency-based analysis of clonogenic survival data. This tool provides functions that enable a robust analysis of colony formation assay (CFA) data in presence or absence of cellular cooperation. The implemented method has been described in Brix et al. (2020). (Brix, N., Samaga, D., Hennel, R. et al. "The clonogenic assay: robustness of plating efficiency-based analysis is strongly compromised by cellular cooperation." Radiat Oncol 15, 248 (2020). <doi:10.1186/s13014-020-01697-y>) Power regression for parameter estimation, calculation of survival fractions, uncertainty analysis and plotting functions are provided.

Provide a series of functions to conduct a meta analysis of factor analysis based on co-occurrence matrices. The tool can be used to solve the factor structure (i.e. inner structure of a construct, or scale) debate in several disciplines, such as psychology, psychiatry, management, education so on. References: Shafer (2005) <doi:10.1037/1040-3590.17.3.324>; Shafer (2006) <doi:10.1002/jclp.20213>; Loeber and Schmaling (1985) <doi:10.1007/BF00910652>.

Plot confidence interval from the objects of statistical tests such as t.test(), var.test(), cor.test(), prop.test() and fisher.test() ('htest class), Tukey test [TukeyHSD()], Dunnett test [glht() in multcomp package], logistic regression [glm()], and Tukey or Games-Howell test [posthocTGH() in userfriendlyscience package]. Users are able to set the styles of lines and points. This package contains the function to calculate odds ratios and their confidence intervals from the result of logistic regression.

Perform variable selection for Cox regression model with interval-censored data. Can deal with both low-dimensional and high-dimensional data. Case-cohort design can be incorporated. Two sets of covariates scenario can also be considered. The references are listed in the URL below.

This package implements collaborative filtering methods for recommendation systems based on user-item interaction data. Supports both explicit feedback (ratings) and implicit feedback (consumption). The package uses efficient sparse matrix representations and provides incremental updates for users, items, and similarity structures through an R6 class-based architecture. See Aggarwal (2016) <doi:10.1007/978-3-319-29659-3> for an overview.

Detection of change-points for variance of heteroscedastic Gaussian variables with piecewise constant variance function. Adelfio, G. (2012), Change-point detection for variance piecewise constant models, Communications in Statistics, Simulation and Computation, 41:4, 437-448, <doi:10.1080/03610918.2011.592248>.

Utility functions that provides wrapper to descriptive base functions like cor, mean and table. It makes use of the formula interface to pass variables to functions. It also provides operators to concatenate (%+%), to repeat (%n%) and manage character vectors for nice display.

This package provides functions that format statistical output in a way that can be inserted into R Markdown documents. This is analogous to the apa_print() functions in the papaja package but prints Markdown or LaTeX syntax.

Core Hunter is a tool to sample diverse, representative subsets from large germplasm collections, with minimum redundancy. Such so-called core collections have applications in plant breeding and genetic resource management in general. Core Hunter can construct cores based on genetic marker data, phenotypic traits or precomputed distance matrices, optimizing one of many provided evaluation measures depending on the precise purpose of the core (e.g. high diversity, representativeness, or allelic richness). In addition, multiple measures can be simultaneously optimized as part of a weighted index to bring the different perspectives closer together. The Core Hunter library is implemented in Java 8 as an open source project (see <http://www.corehunter.org>).

Modelling structural zeros in compositional data assuming a latent Gaussian model, where MLE is performed via the EM algorithm. The relevant paper is Tsagris M. (2026). Modelling structural zeros in compositional data via a zero-censored multivariate normal model. <doi:10.48550/arXiv.2208.13073>.

Stan based functions to estimate CAR-MM models. These models allow to estimate Generalised Linear Models with CAR (conditional autoregressive) spatial random effects for spatially and temporally misaligned data, provided a suitable Multiple Membership matrix. The main references are Gramatica, Liverani and Congdon (2023) <doi:10.1214/23-BA1370>, Petrof, Neyens, Nuyts, Nackaerts, Nemery and Faes (2020) <doi:10.1002/sim.8697> and Gramatica, Congdon and Liverani <doi:10.1111/rssc.12480>.

This is a function for validating microarray clusters via reproducibility, based on the paper referenced below.

Patients Mental Health (MH) status, Substance Use (SU) status, and concurrent MH/SU status in the American/Canadian Healthcare Administrative Databases can be identified. The detection is based on given parameters of interest by clinicians including the list of plausible ICD MH/SU codes (3/4/5 characters), the required number of visits of hospital for MH/SU , the required number of visits of service physicians for MH/SU, and the maximum time span within MH visits, within SU visits, and, between MH and SU visits. Methods are described in: Khan S <https://pubmed.ncbi.nlm.nih.gov/29044442/>, Keen C, et al. (2021) <doi:10.1111/add.15580>, Lavergne MR, et al. (2022) <doi:10.1186/s12913-022-07759-z>, Casillas, S M, et al. (2022) <doi:10.1016/j.abrep.2022.100464>, CIHI (2022) <https://www.cihi.ca/en>, CDC (2024) <https://www.cdc.gov>, WHO (2019) <https://icd.who.int/en>.

This package provides a set of radiative transfer models to quantitatively describe the absorption, reflectance and transmission of solar energy in vegetation, and model remotely sensed spectral signatures of vegetation at distinct spatial scales (leaf,canopy and stand). The main principle behind ccrtm is that many radiative transfer models can form a coupled chain, basically models that feed into each other in a linked chain (from leaf, to canopy, to stand, to atmosphere). It allows the simulation of spectral datasets in the solar spectrum (400-2500nm) using leaf models as PROSPECT5, 5b, and D which can be coupled with canopy models as FLIM', SAIL and SAIL2'. Currently, only a simple atmospheric model ('skyl') is implemented. Jacquemoud et al 2008 provide the most comprehensive overview of these models <doi:10.1016/j.rse.2008.01.026>.

This package 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>.

Canonical correlation analysis and maximum correlation via projection pursuit, as well as fast implementations of correlation estimators, with a focus on robust and nonparametric methods.

Bayesian component model-based network meta-analysis for treatment combinations with explicit component dose-response and dose-dependent interaction surfaces. The main interface fits single-timepoint arm-level networks with continuous or binary outcomes, any number of components, additive, bilinear, or saturating pairwise interactions, study-level random effects, and prediction at unobserved dose combinations. A stage-one longitudinal interface fits a two-component exponential time-course model with a bilinear interaction on the asymptote. Estimation uses Stan through cmdstanr or rstan'. Methods are described in Welton et al. (2009) <doi:10.1093/aje/kwp014>, Mawdsley et al. (2016) <doi:10.1002/psp4.12091>, Wicha et al. (2017) <doi:10.1038/s41467-017-01929-y>, and Pedder et al. (2019) <doi:10.1002/jrsm.1351>.

This package provides a simple interface to pull County Health Rankings & Roadmaps (CHR&R) county-level health data and metadata directly from Zenodo <doi:10.5281/zenodo.18157681>. Users can retrieve data for CHR&R release years 2010 through 2025. CHR&R data support research and decision-making to promote health equity and policies that help all communities thrive.

Convert text into synthesized speech and get a list of supported voices for a region. Microsoft's Cognitive Services Text to Speech REST API <https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-text-to-speech?tabs=streaming> supports neural text to speech voices, which support specific languages and dialects that are identified by locale.

This package implements a specific form of segmented linear regression with two independent variables. The visualization of that function looks like a quarter segment of a cowbell giving the package its name. The package has been specifically constructed for the case where minimum and maximum value of the dependent and two independent variables are known a prior, which is usually the case when those values are derived from Likert scales.

This package provides functions for testing if the covariance structure of 2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e. if covariance(X) = C_1 x C_2. A complete descriptions of the implemented tests can be found in the paper Aston et al. (2017) <doi:10.1214/16-AOS1495> <doi:10.48550/arXiv.1505.02023>.

This package provides methods for difference-in-differences with a continuous treatment and staggered treatment adoption. Includes estimation of treatment effects and causal responses as a function of the dose, event studies indexed by length of exposure to the treatment, and aggregation into overall average effects. Uniform inference procedures are included, along with both parametric and nonparametric models for treatment effects. The methods are based on Callaway, Goodman-Bacon, and Sant'Anna (2025) <doi:10.48550/arXiv.2107.02637>.

Interface to easily access Cropland Data Layer (CDL) data for any area of interest via the CropScape <https://nassgeodata.gmu.edu/CropScape/> web service.