Fits a double logistic function to NDVI time series and calculates instantaneous rate of green (IRG) according to methods described in Bischoff et al. (2012) <doi:10.1086/667590>.
Maximum likelihood estimation and likelihood ratio test are essential for modern statistics. This package supports in calculating likelihood based inference. Reference: Pawitan Y. (2001, ISBN:0-19-850765-8).
Metric halfspace depth for object data, generalizing Tukey's depth for Euclidean data. Implementing the method described in Dai and Lopez-Pintado (2022) <doi:10.1080/01621459.2021.2011298>.
Policy evaluation using generalized Qini curves: Evaluate data-driven treatment targeting rules for one or more treatment arms over different budget constraints in experimental or observational settings under unconfoundedness.
Estimators for multivariate symmetrical uncertainty based on the work of Gustavo Sosa et al. (2016) <arXiv:1709.08730>, total correlation, information gain and symmetrical uncertainty of categorical variables.
Computes Strongest Neighbor Coherence (SNC), a structural diagnostic that replaces Cronbach's alpha using top-k correlation structure. For methodology, see Wells (2025) <https://github.com/TheotherDrWells/snc>.
Fit a regularized generalized linear model via penalized maximum likelihood. The model is fit for a path of values of the penalty parameter. Fits linear, logistic and Cox models.
This package provides an interface to the VK API <https://vk.com/dev/methods>. VK <https://vk.com/> is the largest European online social networking service, based in Russia.
This package provides a menu-driven program and library of functions for carrying out convergence diagnostics and statistical and graphical analysis of Markov chain Monte Carlo (MCMC) sampling output.
This package provides alternative implementations of some base R functions, including sort, order, and match. The functions are simplified but can be faster or have other advantages.
Pretty fast implementation of the Ramer-Douglas-Peucker algorithm for reducing the number of points on a 2D curve. Urs Ramer (1972), "An iterative procedure for the polygonal approximation of plane curves" <doi:10.1016/S0146-664X(72)80017-0>. David H. Douglas and Thomas K. Peucker (1973), "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature" <doi:10.3138/FM57-6770-U75U-7727>.
This package implements state-of-the-art Random Graphical Models (RGMs) for multivariate data analysis across multiple environments, offering tools for exploring network interactions and structural relationships. Capabilities include joint inference across environments, integration of external covariates, and a Bayesian framework for uncertainty quantification. Applicable in various fields, including microbiome analysis. Methods based on Vinciotti, V., Wit, E., & Richter, F. (2023). "Random Graphical Model of Microbiome Interactions in Related Environments." <arXiv:2304.01956>.
Feature Selection with Regularized Random Forest. This package is based on the randomForest package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) <doi:10.48550/arXiv.1306.0237>.
Run basic pattern analyses on character sets, digits, or combined input containing both characters and numeric digits. Useful for data cleaning and for identifying columns containing multiple or nonstandard formats.
This package provides an interface to data provided by the Bank for International Settlements <https://www.bis.org>, allowing for programmatic retrieval of a large quantity of (central) banking data.
Seasonal- and calendar adjustment of time series with daily frequency using the DSA approach developed by Ollech, Daniel (2018): Seasonal adjustment of daily time series. Bundesbank Discussion Paper 41/2018.
Create biplots for GGE (genotype plus genotype-by-environment) and GGB (genotype plus genotype-by-block-of-environments) models. See Laffont et al. (2013) <doi:10.2135/cropsci2013.03.0178>.
Latent budget analysis is a method for the analysis of a two-way contingency table with an exploratory variable and a response variable. It is specially designed for compositional data.
Simple helpers for matrix multiplication on data.frames. These allow for more concise code during low level mathematical operations, and help ensure code is more easily read, understood, and serviced.
This package provides routines for multivariate measurement error correction. Includes procedures for linear, logistic and Cox regression models. Bootstrapped standard errors and confidence intervals can be obtained for corrected estimates.
This package implements Procrustes cross-validation method for Principal Component Analysis, Principal Component Regression and Partial Least Squares regression models. S. Kucheryavskiy (2023) <doi:10.1016/j.aca.2023.341096>.
Following the method of Bailey et al., computes for a collection of candidate models the probability of backtest overfitting, the performance degradation and probability of loss, and the stochastic dominance.
Shewhart quality control charts for continuous, attribute and count data. Cusum and EWMA charts. Operating characteristic curves. Process capability analysis. Pareto chart and cause-and-effect chart. Multivariate control charts.
Estimation of the survivor average causal effect under outcomes truncated by death, which requires the existence of a substitution variable. It can be applied to both experimental and observational data.