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This R package evaluates main and pair-wise interaction effect of single nucleotide polymorphisms (SNPs) via the W-test, scalable to whole genome-wide data sets. The package provides fast and accurate p-value estimation of genetic markers,…

Computation · Statistics 2016-10-12 Rui Sun , Billy Chang , Benny Chung-Ying Zee , Maggie Haitian Wang

Semi-competing risks refer to the setting where primary scientific interest lies in estimation and inference with respect to a non-terminal event, the occurrence of which is subject to a terminal event. In this paper, we present the R…

Computation · Statistics 2018-04-06 Danilo Alvares , Sebastien Haneuse , Catherine Lee , Kyu Ha Lee

Recent advances have shown that statistical tests for the rank of cross-covariance matrices play an important role in causal discovery. These rank tests include partial correlation tests as special cases and provide further graphical…

Machine Learning · Computer Science 2025-06-13 Xinshuai Dong , Ignavier Ng , Boyang Sun , Haoyue Dai , Guang-Yuan Hao , Shunxing Fan , Peter Spirtes , Yumou Qiu , Kun Zhang

This article introduces the bpcs R package (Bayesian Paired Comparison in Stan) and the statistical models implemented in the package. This package aims to facilitate the use of Bayesian models for paired comparison data in behavioral…

Methodology · Statistics 2021-09-21 David Issa Mattos , Érika Martins Silva Ramos

Factorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process response. In the statistics literature, several studies have…

Methodology · Statistics 2020-12-16 Pratishtha Batra , Neil A. Spencer , Pritam Ranjan

The BayesBinMix package offers a Bayesian framework for clustering binary data with or without missing values by fitting mixtures of multivariate Bernoulli distributions with an unknown number of components. It allows the joint estimation…

Computation · Statistics 2017-07-03 Panagiotis Papastamoulis , Magnus Rattray

A depth-based rank sum statistic for multivariate data introduced by Liu and Singh [J. Amer. Statist. Assoc. 88 (1993) 252--260] as an extension of the Wilcoxon rank sum statistic for univariate data has been used in multivariate rank tests…

Statistics Theory · Mathematics 2011-11-10 Yijun Zuo , Xuming He

Conducting research often involves managing multiple disconnected tools for survey design, data collection, response analysis, and report generation, leading to inefficiencies, increased error risks, and challenges in ensuring…

Computation · Statistics 2025-08-11 Clievins Selva

Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed…

Applications · Statistics 2014-09-30 Alexey Miroshnikov , Erin Conlon

Clustering is widely used in unsupervised learning to find homogeneous groups of observations within a dataset. However, clustering mixed-type data remains a challenge, as few existing approaches are suited for this task. This study…

Machine Learning · Statistics 2025-11-26 Badih Ghattas , Alvaro Sanchez San-Benito

We propose new smoothed median and the Wilcoxon's rank sum test. As is pointed out by Maesono et al.(2016), some nonparametric discrete tests have a problem with their significance probability. Because of this problem, the selection of the…

Statistics Theory · Mathematics 2024-07-19 Taku Moriyama , Yoshihiko Maesono

Advancements in medical informatics tools and high-throughput biological experimentation make large-scale biomedical data routinely accessible to researchers. Competing risks data are typical in biomedical studies where individuals are at…

Computation · Statistics 2021-11-30 Eric S Kawaguchi , Jenny I Shen , Gang Li , Marc A Suchard

This contribution presents a guide to the R package multilevLCA, which offers a complete and innovative set of technical tools for the latent class analysis of single-level and multilevel categorical data. We describe the available model…

Computation · Statistics 2024-04-11 Johan Lyrvall , Roberto Di Mari , Zsuzsa Bakk , Jennifer Oser , Jouni Kuha

The evaluation of clustering algorithms can involve running them on a variety of benchmark problems, and comparing their outputs to the reference, ground-truth groupings provided by experts. Unfortunately, many research papers and graduate…

Machine Learning · Computer Science 2023-10-27 Marek Gagolewski

Background: Time-to-event data with multiple time scales are observed in many epidemiological and clinical studies. While models that allow for simultaneous consideration of multiple time scales for the hazard of an event have been…

Methodology · Statistics 2026-03-16 Angela Carollo , Paul H. C. Eilers , Hein Putter , Jutta Gampe

CUSUMs based on the signed sequential ranks of observations are developed for detecting location and scale changes in symmetric distributions. The CUSUMs are distribution free and fully self-starting: given a specified in-control median and…

Methodology · Statistics 2017-06-14 F. Lombard , C. Van Zyl

Ranked set sampling (RSS) is a stratified sampling method that improves efficiency over simple random sampling (SRS) by utilizing auxiliary information for ranking and stratification. While balanced RSS (BRSS) assumes equal allocation…

Methodology · Statistics 2025-09-03 Chul Moon , Soohyun Ahn

A new family of nonparametric statistics, the r-statistics, is introduced. It consists of counting the number of records of the cumulative sum of the sample. The single-sample r-statistic is almost as powerful as Student's t-statistic for…

Methodology · Statistics 2015-07-14 Damien Challet

Basket trials are a new type of clinical trial in which a treatment is investigated in several subgroups. For the analysis of these trials, information is shared between the subgroups based on the observed data to increase the power. Many…

Computation · Statistics 2024-03-27 Lukas Baumann

Motivation: Bulk RNA-Seq is a widely used method for studying gene expression across a variety of contexts. The significance of RNA-Seq studies has grown with the advent of high-throughput sequencing technologies. Computational methods have…

Genomics · Quantitative Biology 2025-03-28 Juliana Costa-Silva , David Menotti , Fabricio M. Lopes