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Accounting for Missing Actors in Interaction Network Inference from Abundance Data

https://doi.org/10.1111/rssc.12509
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A review of multivariate distributions for count data derived from the Poisson distribution
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It’s DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR
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Tractable Bayesian learning of tree belief networks
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A general algorithm for covariance modeling of discrete data
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Linear Model Selection by Cross-Validation
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Variational Inference: A Review for Statisticians
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Fish assemblages in the Barents Sea
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Composite likelihood methods
inferredcites →https://doi.org/10.1093/biomet/76.4.643openalex-snapshot
The Multivariate Poisson-Log Normal Distribution
inferredcites →https://doi.org/10.1093/biostatistics/kxm045openalex-snapshot
Sparse inverse covariance estimation with the graphical lasso
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Graphical Models
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Assessing a mixture model for clustering with the integrated completed likelihood
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Approximating discrete probability distributions with dependence trees
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Untangling direct species associations from indirect mediator species effects with graphical models
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Tree‐based inference of species interaction networks from abundance data
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Spatial Interaction and the Statistical Analysis of Lattice Systems
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
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Rank-Sparsity Incoherence for Matrix Decomposition
inferredcites →https://doi.org/10.1137/18m1211350openalex-snapshot
Sparse Principal Component Analysis via Variable Projection
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Robust principal component analysis?
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Sampling random spanning trees faster than matrix multiplication
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Multiple precision arithmetic
inferredcites →https://doi.org/10.1177/1471082x18786289openalex-snapshot
Incomplete graphical model inference via latent tree aggregation
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A scaling normalization method for differential expression analysis of RNA-seq data
inferredcites →https://doi.org/10.1186/s12918-016-0313-0openalex-snapshot
XMRF: an R package to fit Markov Networks to high-throughput genetics data
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Inferring sparse Gaussian graphical models with latent structure
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A survey of cross-validation procedures for model selection
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Discussion: Latent variable graphical model selection via convex optimization
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Discussion: Latent variable graphical model selection via convex optimization
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Variational inference for probabilistic Poisson PCA
inferredcites →https://doi.org/10.1214/aos/1176344136openalex-snapshot
Estimating the Dimension of a Model
inferredcites →https://doi.org/10.1561/2200000001openalex-snapshot
Graphical Models, Exponential Families, and Variational Inference
inferredcites →https://doi.org/10.1561/9781601981851openalex-snapshot
Graphical Models, Exponential Families, and Variational Inference
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The ade4 Package: Implementing the Duality Diagram for Ecologists
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The EM Algorithm and Extensions
inferredcites →https://doi.org/10.32614/cran.package.gmpopenalex-snapshot
gmp: Multiple Precision Arithmetic
inferredcites →https://doi.org/10.32614/cran.package.poilogopenalex-snapshot
poilog: Poisson Lognormal and Bivariate Poisson Lognormal Distribution
inferredcites →https://doi.org/10.48550/arxiv.1406.2721openalex-snapshot
Learning Latent Variable Gaussian Graphical Models
inferredcites →https://doi.org/10.48550/arxiv.1603.03629openalex-snapshot
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies
inferredcites →https://doi.org/10.48550/arxiv.1806.03120openalex-snapshot
Variational inference for sparse network reconstruction from count data
inferredcites →https://doi.org/10.48550/arxiv.1901.00886openalex-snapshot
Nonparametric graphical model for counts
inferredcites →https://doi.org/10.48550/arxiv.2006.14781openalex-snapshot
The huge Package for High-dimensional Undirected Graph Estimation in R
inferredcites →https://doi.org/10.5555/2188385.2343681openalex-snapshot
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inferredcites →https://doi.org/10.6084/m9.figshare.5203696openalex-snapshot
Variational Inference: A Review for Statisticians
inferredcites →https://doi.org/10.7551/mitpress/7503.001.0001openalex-snapshot
Advances in Neural Information Processing Systems 19

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4755176openalex-extracted
Inferring Stochastic Group Interactions within Structured Populations Via Coupled Autoregression
inferred← citeshttps://doi.org/10.1016/j.jtbi.2024.111793openalex-snapshot
Inferring stochastic group interactions within structured populations via coupled autoregression
inferred← citeshttps://doi.org/10.1016/j.tree.2021.01.002openalex-snapshot
On the Interpretations of Joint Modeling in Community Ecology
inferred← citeshttps://doi.org/10.1098/rspa.2023.0284openalex-snapshot
Complex systems in ecology: a guided tour with large Lotka–Volterra models and random matrices
inferred← citeshttps://doi.org/10.1101/2025.07.24.666553openalex-snapshot
Zero-inflated Joint Species Distribution Models for improved partial-correlation network inference from community data
inferred← citeshttps://doi.org/10.70675/a631122czb60az4d31za3edzd4d75ac24d4eopenalex-snapshot
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