MultiCOAP
1.1High-Dimensional Covariate-Augmented Overdispersed Multi-Study Poisson Factor Model
Overview
We introduce factor models designed to jointly analyze high-dimensional count data from multiple studies by extracting study-shared and specified factors. Our factor models account for heterogeneous noises and overdispersion among counts with augmented covariates. We propose an efficient and speedy variational estimation procedure for estimating model parameters, along with a novel criterion for selecting the optimal number of factors and the rank of regression coefficient matrix. More details can be referred to Liu et al. (2024) doi:10.48550/arXiv.2402.15071.
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- Documented parameters
- 85%
- Return-value docs
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- References docs
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1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2024-03-07
- Total releases
- 1 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 14 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet