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Related papers: Infinite joint species distribution models

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We study a model ecosystem by means of dynamical techniques from disordered systems theory. The model describes a set of species subject to competitive interactions through a background of resources, which they feed upon. Additionally…

Populations and Evolution · Quantitative Biology 2009-11-13 Yoshimi Yoshino , Tobias Galla , Kei Tokita

This paper takes a quick look at Bayesian joint models (BJM) for longitudinal and survival data. A general formulation for BJM is examined in terms of the sampling distribution of the longitudinal and survival processes, the conditional…

Methodology · Statistics 2020-05-27 Carmen Armero

Joint models for longitudinal and survival data have gained a lot of attention in recent years, with the development of myriad extensions to the basic model, including those which allow for multivariate longitudinal data, competing risks…

Methodology · Statistics 2020-03-09 Katya Mauff , Ewout Steyerberg , Isabella Kardys , Eric Boersma , Dimitris Rizopoulos

A common theme underlying many problems in statistics and economics involves the determination of a systematic method of selecting a joint distribution consistent with a specified list of categorical marginals, some of which have an ordinal…

Theoretical Economics · Economics 2025-10-08 Christopher P. Chambers , Yusufcan Masatlioglu , Ruodu Wang

We consider deep multivariate models for heterogeneous collections of random variables. In the context of computer vision, such collections may e.g. consist of images, segmentations, image attributes, and latent variables. When developing…

Machine Learning · Computer Science 2026-02-03 Dmitrij Schlesinger , Boris Flach , Alexander Shekhovtsov

Given samples from a distribution, how many new elements should we expect to find if we continue sampling this distribution? This is an important and actively studied problem, with many applications ranging from unseen species estimation to…

Machine Learning · Computer Science 2017-07-14 Aditi Raghunathan , Greg Valiant , James Zou

We review recent work aimed at modeling species extinction over geological time. We discuss a number of models which, rather than dealing with the direct causes of particular extinction events, attempt to predict overall statistical trends,…

adap-org · Physics 2015-06-30 M. E. J. Newman , R. G. Palmer

Species distribution models (SDMs) are widely used to predict species' geographic distributions, serving as critical tools for ecological research and conservation planning. Typically, SDMs relate species occurrences to environmental…

Machine Learning · Computer Science 2025-08-12 Hager Radi Abdelwahed , Mélisande Teng , Robin Zbinden , Laura Pollock , Hugo Larochelle , Devis Tuia , David Rolnick

Finite mixture distributions arise in sampling a heterogeneous population. Data drawn from such a population will exhibit extra variability relative to any single subpopulation. Statistical models based on finite mixtures can assist in the…

Methodology · Statistics 2024-01-19 Andrew M. Raim , Nagaraj K. Neerchal , Jorge G. Morel

Diversification models describe the random growth of evolutionary trees, modeling the historical relationships of species through speciation and extinction events. One class of such models allows for independently changing traits, or types,…

Statistics Theory · Mathematics 2022-06-22 Dakota Dragomir , Elizabeth S. Allman , John A. Rhodes

Joint distributions over many variables are frequently modeled by decomposing them into products of simpler, lower-dimensional conditional distributions, such as in sparsely connected Bayesian networks. However, automatically learning such…

Machine Learning · Computer Science 2013-01-07 Scott Davies , Andrew Moore

We provide finite-sample distribution approximations, that are uniform in the parameter, for inference in linear mixed models. Focus is on variances and covariances of random effects in cases where existing theory fails because their…

Statistics Theory · Mathematics 2025-07-29 Karl Oskar Ekvall , Matteo Bottai

Studies on distribution, abundance and diversity of species revealed fascinating universalities in macroecology. Many of these patterns, like the species-area and range-abundance relationship or the year-to-year fluctuations in population…

Populations and Evolution · Quantitative Biology 2007-05-23 M. Ravasz , A. Balog , V. Marko , Z. Neda

A reparametrized Dirichlet-multinomial distribution is introduced, and the covariance matrix, as well as, the algorithm for calculating the PDF for n species are provided. The distribution is suited for modelling the joint distribution of…

Populations and Evolution · Quantitative Biology 2020-03-04 Christian Damgaard

Multivariate count data are defined as the number of items of different categories issued from sampling within a population, which individuals are grouped into categories. The analysis of multivariate count data is a recurrent and crucial…

Machine Learning · Statistics 2013-12-17 Pierre Fernique , Jean-Baptiste Durand , Yann Guédon

Using a sample from a population to estimate the proportion of the population with a certain category label is a broadly important problem. In the context of microbiome studies, this problem arises when researchers wish to use a sample from…

Methodology · Statistics 2019-02-08 Bryan D. Martin , Daniela Witten , Amy D. Willis

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world…

Methodology · Statistics 2016-12-28 David I. Inouye , Eunho Yang , Genevera I. Allen , Pradeep Ravikumar

Phylogenetic diversity is a measure for describing how much of an evolutionary tree is spanned by a subset of species. If one applies this to the (unknown) subset of current species that will still be present at some future time, then this…

Subcellular Processes · Quantitative Biology 2009-09-29 Beata Faller , Fabio Pardi , Mike Steel

1. Joint Species Distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations, and possibly spatially structured residual covariance. They show great promise as a…

Quantitative Methods · Quantitative Biology 2023-03-28 Maximilian Pichler , Florian Hartig

Several methods have recently been developed for joint structure learning of multiple (related) graphical models or networks. These methods treat individual networks as exchangeable, such that each pair of networks are equally encouraged to…

Methodology · Statistics 2014-06-03 Chris J. Oates , Sach Mukherjee
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