An implementation of distributional random forests as introduced in Cevid & Michel & Meinshausen & Buhlmann (2020) <arXiv:2005.14458>.
Robust Estimation of Multivariate Location and Scatter in the Presence of Cellwise and Casewise Contamination and Missing Data.
This package provides functions to generate and analyze data for psychology experiments based on the General Recognition Theory.
This package provides methods for estimation and statistical inference on directional and fluctuating selection in age-structured populations.
Fractional polynomials are used to represent curvature in regression models. A key reference is Royston and Altman, 1994.
Naive discriminative learning implements learning and classification models based on the Rescorla-Wagner equations and their equilibrium equations.
The Semi Parametric Piecewise Distribution blends the Generalized Pareto Distribution for the tails with a kernel based interior.
Relaxed Radix Balanced Trees are an immutable vector-like data structure with good performance characteristics for concatenation and slicing.
This package performs penalized multivariate analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis.
This package implements heuristics for the quadratic assignment problem (QAP). Currently only a simulated annealing heuristic is available.
ReTux is an action platformer loosely inspired by the Mario games, utilizing the art assets from the SuperTux project.
An easy-to-use tool to employ interactivity in every-day exploratory analysis. It contains a collection of most commonly used types of charts (such as scatter plots, line plots, heatmaps, bar charts), which can be linked to each other or to other interactive elements with just few lines of code.
Random forest with a variety of additional features for regression, classification and survival analysis. The features include: parallel computing with OpenMP, embedded model for selecting the splitting variable, based on Zhu, Zeng & Kosorok (2015) <doi:10.1080/01621459.2015.1036994>, subject weight, variable weight, tracking subjects used in each tree, etc.
Fits novel models for the conditional relative risk, risk difference and odds ratio <doi:10.1080/01621459.2016.1192546>.
This package provides a collection of functions which aim to assist common computational workflow for analysis of matabolomic data..
Collection of functions related to benchmark with prediction models for data analysis and editing of clinical and epidemiological data.
R implementations of standard financial engineering codes; vanilla option pricing models such as Black-Scholes, Bachelier, CEV, and SABR.
This package provides functions to perform dimensionality reduction for classification if the covariance matrices of the classes are unequal.
Constructs trees for multivariate survival data using marginal and frailty models. Grows, prunes, and selects the best-sized tree.
Uses a modified lifting algorithm on which it builds the nondecimated lifting transform. It has applications in wavelet shrinkage.
Computes probabilities of the bivariate normal distribution in a vectorized R function (Drezner & Wesolowsky, 1990, <doi:10.1080/00949659008811236>).
Piecewise constant hazard models for survival data. The package allows for right-censored, left-truncated, and interval-censored data.
Generates synonyms from a given word drawing from a synonym list from the moby project <http://moby-thesaurus.org/>.
Boosting the likelihood of conditional and shift transformation models as introduced in <DOI:10.1007/s11222-019-09870-4>.