Search results for "Latent variable"

Using latent variable models to identify large networks of species‐to‐species associations at different spatial scales

2015

Summary We present a hierarchical latent variable model that partitions variation in species occurrences and co-occurrences simultaneously at multiple spatial scales. We illustrate how the parameterized model can be used to predict the occurrences of a species by using as predictors not only the environmental covariates, but also the occurrences of all other species, at all spatial scales. We leverage recent progress in Bayesian latent variable models to implement a computationally effective algorithm that enables one to consider large communities and extensive sampling schemes. We exemplify the framework with a community of 98 fungal species sampled in c. 22 500 dead wood units in 230 plot…

gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models inr

2019

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.

Model‐based approaches to unconstrained ordination

2014

Summary Unconstrained ordination is commonly used in ecology to visualize multivariate data, in particular, to visualize the main trends between different sites in terms of their species composition or relative abundance. Methods of unconstrained ordination currently used, such as non-metric multidimensional scaling, are algorithm-based techniques developed and implemented without directly accommodating the statistical properties of the data at hand. Failure to account for these key data properties can lead to misleading results. A model-based approach to unconstrained ordination can address this issue, and in this study, two types of models for ordination are proposed based on finite mixtu…

Efficient estimation of generalized linear latent variable models.

2019

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…

Variational Approximations for Generalized Linear Latent Variable Models

2017

Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal likelihood does not possess a closed form for nonnormal responses. We propose a variational approximation (VA) method for estimating GLLVMs. For the common cases of binary, ordinal, and overdispersed count data, we derive fully closed-form approximations to the marginal log-likelihood function in each case. Compared to other methods such as the expectation-maximization algorithm, estimation using VA is fast and straightforward to implement. Predictions of the latent variabl…

Extending Joint Models in Community Ecology : A Response to Beissinger et al.

2016

The joint modelling of many variables in community ecology is a new and technically challenging area with many opportunities for future developments. The possibility of extending joint models to deal with imperfect detection has been highlighted by Beissinger et al. as an important problem worthy of further investigation [1]. We agree, and previously pointed to this potential extension as an outstanding question [2], alongside models that can estimate phylogenetic repulsion or attraction, nonlinearity in the response to latent variables, and spatial or temporal correlation, because further developments in all these directions are needed.

Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders

2020

This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Further, versatility is added by conditioning on the speed, extending the VAE to a conditional VAE (CVAE), thereby incorporating all speeds in a single model. Within the framework, the coefficients of autoregressive (AR) models are used as features. The dimensionality reduction inherent in the proposed method lowers the need of expert knowledge to design good condition indicators. Moreover, the sugg…

2017

The analysis of open-minded attitudes towards sexuality in general requires a construct based on attitudinal dimensions. Although several existing studies involve sexual attitudes, they differ substantially and standardized conceptual work is missing. Thus, the authors introduce the latent variable sexual openness to develop a construct based on self-oriented attitudes towards different sexual topics. Available survey data of female German students in a steady relationship allowed providing a first empirical test for the applicability of this construct. Five subdimensions are acknowledged central for sexual openness: sexual practices, masturbation, bisexuality, permissiveness, and pornograp…

The WHO-5 Well-Being Index – Validation based on item response theory and the analysis of measurement invariance across 35 countries.

2020

Abstract Background The five-item World Health Organization Well-Being Index (WHO-5) is a frequently used brief standard measure in large-scale cross-cultural clinical studies. Despite its frequent use, some psychometric questions remain that concern the choice of an adequate item response theory (IRT) model, the evaluation of reliability at important cutoff points, and most importantly the assessment of measurement invariance across countries. Methods Data from the 6th European Working Condition survey (2015) were used that collected nationally representative samples of employed and self-employed individuals (N = 43,469) via computer-aided personal interviews across 35 European countries. …

Teacher Support Resources, Need Satisfaction and Well-Being.

2015

AbstractBased on Job Demands-Resources Model (JD-R), this study examines the relationships among teacher support resources, psychological need satisfaction, engagement and burnout in a sample of 282 Spanish secondary school teachers. Nine teacher psychological needs were identified based on the study of Bess and on the Self-Determination Theory (SDT). Self-report questionnaires were used to measure the constructs selected for this study and their interrelationships were examined by structural equation modeling. The results reveal a good model fit to the data (NNFI = .88; CFI = .90; GFI = .90; RMSEA = .061). The analyses indicate a positive and significant effect of latent variable Psycholog…