0000000001278143
AUTHOR
Jenni Niku
Efficient estimation of generalized linear latent variable models.
Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estim…
Fast and universal estimation of latent variable models using extended variational approximations
AbstractGeneralized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ecology. One of the main features of GLLVMs is their capacity to handle a variety of responses types, such as (overdispersed) counts, binomial and (semi-)continuous responses, and proportions data. On the other hand, the inclusion of unobserved latent variables poses a major computational challenge, as the resulting marginal likelihood function involves an intractable integral for non-normally distributed responses. This has spurred research into a number of approx…
Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models
In ecological community studies it is often of interest to study the effect of species related trait variables on abundances or presence-absences. Specifically, the interest may lay in the interactions between environmental and trait variables. An increasingly popular approach for studying such interactions is to use the so-called fourth-corner model, which explicitly posits a regression model where the mean response of each species is a function of interactions between covariate and trait predictors (among other terms). On the other hand, many of the fourth-corner models currently applied in the literature are too simplistic to properly account for variation in environmental and trait resp…
gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models inr
The work of J.N. was supported by the Wihuri Foundation. The work of S.T. was supported by the CRoNoS COST Action IC1408.F.K.C.H. was also supported by an ANU cross disciplinary grant.
gllvm : Fast analysis of multivariate abundance data with generalized linear latent variable models in R
1.There has been rapid development in tools for multivariate analysis based on fully specified statistical models or “joint models”. One approach attracting a lot of attention is generalized linear latent variable models (GLLVMs). However, software for fitting these models is typically slow and not practical for large datsets. 2.The R package gllvm offers relatively fast methods to fit GLLVMs via maximum likelihood, along with tools for model checking, visualization and inference. 3.The main advantage of the package over other implementations is speed e.g. being two orders of magnitude faster, and capable of handling thousands of response variables. These advances come from using variationa…
Testate amoebae community analysis as a tool to assess biological impacts of peatland use
As most ecosystems, peatlands have been heavily exploited for different human purposes. For example, in Finland the majority is under forestry, agriculture or peat mining use. Peatlands play an important role in carbon storage, water cycle, and are a unique habitat for rare organisms. Such properties highlight their environmental importance and the need for their restoration. To monitor the success of peatland restoration sensitive indicators are needed. Here we test whether testate amoebae can be used as a reliable bioindicator for assessing peatland condition. To qualify as reliable indicators, responses in testate amoebae community structure to ecological changes must be stronger than ra…