A collection of Poisson lognormal models for multivariate count data analysis

OUTRIDER: OUTlier in RNA-seq fInDER is an R-based framework to find aberrantly expressed genes in RNA-seq data

📉 JavaScript Text Statistics that counts lines, words, chars, and spaces.

rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

R Package With Shiny App to Perform and Visualize Clustering of Count Data via Mixtures of Multivariate Poisson-log Normal Model

Analysing Capture Seq Count Data

Official Implementation of Paper "Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling" (ICML 2023)

R Package to Perform Clustering of Three-way Count Data Using Mixtures of Matrix Variate Poisson-log Normal Model With Parameter Estimation via MCMC-EM, Variational Gaussian Approximations, or a Hybrid Approach Combining Both.

Semiparametric and parametric estimation and bootstrapping of integer-valued autoregressive (INAR) models.

Modeling correlated count data

Text Statistics For Node Streams

R package for flexible univariate count models based on renewal processes

Mixed Poisson Regression for Overdispersed Count Data

ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. Takes in the complete filtered and normalized read count matrix, the location of the two sub-populations and the number of cores to be used.

Web Programming Class | Final Project | Campus Assignment

Generation, estimation and testing of INteger Autoregressive models

Mortality Rate Prediction based on Age and Cigarette Types in Canada using Generalized Linear Model for Count Data

Minimal network meta-analysis with BUGS from R.

R package for model-based causal discovery for zero-inflated count data