A collection of Poisson lognormal models for multivariate count data analysis
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Updated
May 6, 2024 - R
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.
Modeling correlated count data
Semiparametric and parametric estimation and bootstrapping of integer-valued autoregressive (INAR) models.
Text Statistics For Node Streams
R package for flexible univariate count models based on renewal processes
Mixed Poisson Regression for Overdispersed Count Data
Generation, estimation and testing of INteger Autoregressive models
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.
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.
Web Programming Class | UPN Veteran Jatim | Website-Bot Register for Robotics community | Final Project
Analysis of seasonal habitat-use patterns of Aldabra giant tortoises of Aldabra Atoll, Seychelles using temporary emigration models.
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