Results 11 to 20 of about 791,274 (314)
Frontiers in Nutrition, 2021 This review uses person-centered research and data analysis strategies to discuss the conceptualization and measurement of appetite self-regulation (ASR) phenotypes and trajectories in childhood (from infancy to about ages 6 or 7 years). Research that is
Alan Russell +2 more
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A Bayesian latent mixture model approach to assessing performance in stock-flow reasoning
Judgment and Decision Making, 2017 People often perform poorly on stock-flow reasoning tasks, with many (but not all) participants appearing to erroneously match the accumulation of the stock to the inflow – a response pattern attributed to the use of a “correlation heuristic”. Efforts to
Arthur Kary +3 more
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flexCWM: A Flexible Framework for Cluster-Weighted Models
Journal of Statistical Software, 2018 Cluster-weighted models (CWMs) are mixtures of regression models with random covariates. However, besides having recently become rather popular in statistics and data mining, there is still a lack of support for CWMs within the most popular statistical ...
Angelo Mazza +2 more
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Computational aspects of N-mixture models [PDF]
, 2015 The N-mixture model is widely used to estimate the abundance of a population in the presence of unknown detection probability from only a set of counts subject to spatial and temporal replication (Royle, 2004, Biometrics 60,105–115).
Morgan, Byron J. T. +3 more
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Deep Gaussian mixture models [PDF]
Statistics and Computing, 2017 Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, Deep Gaussian Mixture Models are introduced and discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple layers of latent variables, where, at each layer, the variables ...
Cinzia Viroli, Geoffrey J. McLachlan
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IEEE Access, 2018 The destructive effects of cyber-attacks demand more proactive security approaches. One such promising approach is the idea of collaborative intrusion detection systems (CIDSs).
Carlos Garcia Cordero +6 more
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How to fit models of recognition memory data using maximum likelihood.
International Journal of Psychological Research, 2010 The aim of this paper is to provide an introductory tutorial to how to fit different models of recognition memory using maximum likelihood estimation. It is in four main parts.
John C. Dunn
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Perfect posterior simulation for mixture and hidden Markov models [PDF]
, 2010 In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models.
Berthelsen, Kasper Klitgaard +6 more
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Machine Learning based on Probabilistic Models Applied to Medical Data: The Case of Prostate Cancer
Journal of Innovation Information Technology and Application, 2023 The growth in the amount of data in companies puts analysts in difficulties when extracting hidden knowledge from data. Several models have emerged that focus on the notion of distances while ignoring the notion of conditional probability density.
Anaclet Tshikutu Bikengela +4 more
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Dealing with Label Switching in Mixture Models Under Genuine Multimodality [PDF]
, 2008 The fitting of finite mixture models is an ill-defined estimation problem as completely different parameterizations can induce similar mixture distributions.
Leisch, Friedrich, Grün, Bettina
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