Search results for "Mixture model"
showing 10 items of 86 documents
Multimodal Mean Adaptive Backgrounding for Embedded Real-Time Video Surveillance
2007
Automated video surveillance applications require accurate separation of foreground and background image content. Cost sensitive embedded platforms place realtime performance and efficiency demands on techniques to accomplish this task. In this paper we evaluate pixel-level foreground extraction techniques for a low cost integrated surveillance system. We introduce a new adaptive technique, multimodal mean (MM), which balances accuracy, performance, and efficiency to meet embedded system requirements. Our evaluation compares several pixel-level foreground extraction techniques in terms of their computation and storage requirements, and functional accuracy for three representative video sequ…
The effect of physical education students' beliefs and values on their physical activity: A growth mixture modelling approach
2013
This study examined the change in adolescents' expectancy-related beliefs and task values towards physical education (PE). In addition, the physical activity (PA) growth trajectories of the identified adolescent subpopulations were examined. This study comprised 812 students (age M = 12.31, range: 11–13), who answered questionnaires four times during Grades 6–9. This study found that expectancy-related beliefs declined, while task values increased across the middle school transition. Adolescents who valued PE highly and experienced an increase in their expectancy-related beliefs became physically more active across time, while adolescents with the lowest levels and the most negative change …
Trajectories of depressive symptoms during emerging adulthood: Antecedents and consequences
2008
In order to examine what kinds of trajectories of depressive symptoms young adults show during emerging adulthood, and their antecedents and consequences, 297 university students completed the revised Beck's depression inventory seven times over a 10-year period, and other measures at the beginning and the end of the study. The growth mixture modelling for depressive symptoms ended up in a 3-group solution: 23% of the participants were typified by a low level of symptoms, 61% showed a moderate level, and 16% fell into the third group with high and increasing levels of depressive symptoms during emerging adulthood. Those on the high-depressive trajectory had a poorer quality of relationships…
The effectiveness of increased support in reading and its relationship to teachers' affect and children's motivation
2016
Abstract The aims of this study were, firstly, to identify different groups of teacher–child dyads on the basis of the longitudinal associations between teachers' individual support in reading and children's reading skills, and, secondly, to examine whether the groups thus identified differ with respect to various teacher- and child-related factors. A total of 372 teacher–child dyads were examined. The reading skills of 6- to 7-year-old Finnish-speaking children were measured at the beginning and end of Grade 1. The amount of teachers' support in reading for a particular child was gathered from teachers by questionnaires. Regression Mixture Modeling identified three latent groups of teacher…
Genetic parameters for somatic cell score according to udder infection status in Valle del Belice dairy sheep and impact of imperfect diagnosis of in…
2010
Abstract Background Somatic cell score (SCS) has been promoted as a selection criterion to improve mastitis resistance. However, SCS from healthy and infected animals may be considered as separate traits. Moreover, imperfect sensitivity and specificity could influence animals' classification and impact on estimated variance components. This study was aimed at: (1) estimating the heritability of bacteria negative SCS, bacteria positive SCS, and infection status, (2) estimating phenotypic and genetic correlations between bacteria negative and bacteria positive SCS, and the genetic correlation between bacteria negative SCS and infection status, and (3) evaluating the impact of imperfect diagno…
Ranking Scientific Journals Via Latent Class Models for Polytomous Item Response Data
2015
Summary We propose a model-based strategy for ranking scientific journals starting from a set of observed bibliometric indicators that represent imperfect measures of the unobserved ‘value’ of a journal. After discretizing the available indicators, we estimate an extended latent class model for polytomous item response data and use the estimated model to cluster journals. We illustrate our approach by using the data from the Italian research evaluation exercise that was carried out for the period 2004–2010, focusing on the set of journals that are considered relevant for the subarea statistics and financial mathematics. Using four bibliometric indicators (IF, IF5, AIS and the h-index), some…
Generalization of Jeffreys Divergence-Based Priors for Bayesian Hypothesis Testing
2008
Summary We introduce objective proper prior distributions for hypothesis testing and model selection based on measures of divergence between the competing models; we call them divergence-based (DB) priors. DB priors have simple forms and desirable properties like information (finite sample) consistency and are often similar to other existing proposals like intrinsic priors. Moreover, in normal linear model scenarios, they reproduce the Jeffreys–Zellner–Siow priors exactly. Most importantly, in challenging scenarios such as irregular models and mixture models, DB priors are well defined and very reasonable, whereas alternative proposals are not. We derive approximations to the DB priors as w…
Sample Size Requirements of a Mixture Analysis Method with Applications in Systematic Biology
1999
The available information on sample size requirements of mixture analysis methods is insufficient to permit a precise evaluation of the potential problems facing practical applications of mixture analysis. We use results from Monte Carlo simulation to assess the sample size requirements of a simple mixture analysis method under conditions relevant to biological applications of mixture analysis. The mixture model used includes two univariate normal components with equal variances but assumes that the researcher is ignorant as to the equality of the variances. The method used relies on the EM algorithm to compute the maximum likelihood estimates of the mixture parameters, and the likelihood r…
GAMLSS for high-variability data: an application to liver fibrosis case
2020
In this paper, we propose management of the problem caused by overdispersed data by applying the generalized additive model for location, scale and shape framework (GAMLSS) as introduced by Rigby and Stasinopoulos (2005). The idea of using a GAMLSS approach for handling our problem comes from the idea of Aitkin (1996) consisting in the use of an EM maximum likelihood estimation algorithm (Dempster, Laird, and Rubin, 1977) to deal with overdispersed generalized linear models (GLM). As in the GLM case, the algorithm is initially derived as a form of Gaussian quadrature assuming a normal mixing distribution. The GAMLSS specification allows the extension of the Aitkin algorithm to probability d…
Functional Brain Segmentation Using Inter-Subject Correlation in fMRI
2016
The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily‐life situations. A new exploratory data‐analysis approach, functional segmentation inter‐subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is h…