Search results for " latent Markov model"

showing 4 items of 4 documents

The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach

2021

This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a trivariate reduction technique and a hidden Markov chain approach. The model allows for disentangling unobservable time-varying heterogeneity from the dynamic effect of utilisation of primary and secondary care and measuring their potential substitution effect. Three points of supports adequately describe the distribution of the latent states suggesting the existence of three profiles of low, medium and high users who shows persistency in their behaviour, but not permanence as some switch to their neighbour's profile.

Economics and Econometrics050208 financeComputer science05 social sciencesExtension (predicate logic)Bivariate analysis01 natural sciencesUnobservablePrimary and Secondary Care Latent Markov ModelSecondary careReduction (complexity)010104 statistics & probability0502 economics and businessEconometricsSubstitution effect0101 mathematics050207 economicsHidden Markov modelSocial Sciences (miscellaneous)Count dataPanel dataJournal of Applied Econometrics
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Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R

2019

Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidden (latent) Markov models (HMMs) are able to detect underlying latent structures and they can be used in various longitudinal settings: to account for measurement error, to detect unobservable states, or to compress information across several types of observations. Extending to mixture hidden Markov models (MHMMs) allows clustering data into homogeneous subsets, with or without external covariate…

FOS: Computer and information sciencesStatistics and ProbabilityMultivariate statisticssequence analysisaikasarjatComputer sciencerMarkov modelStatistics - ComputationStatistics - Applications01 natural sciencesUnobservablecategorical time seriesR-kieli010104 statistics & probabilitymulti-channel sequences; categorical time series; visualizing sequence data; visualizing models; latent Markov models; latent class models; RCovariateApplications (stat.AP)Sannolikhetsteori och statistikComputer software0101 mathematicsTime seriesProbability Theory and StatisticsHidden Markov modelCluster analysislcsh:Statisticslcsh:HA1-4737Categorical variableComputation (stat.CO)ta112business.industryvisualizing sequence dataR (programming languages)Pattern recognitionmulti-channel sequencesvisualizing modelslatent class modelssekvenssianalyysiArtificial intelligencelatent markov modelstime seriesStatistics Probability and UncertaintybusinessSoftwareJournal of Statistical Software
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Patterns of poverty among elderly Americans: a Latent Class Markov Model

2017

ABSTRACTThis article studies poverty persistence and the role of social security programmes on poverty among elderly in the US. We use a Latent Markov model to disentangle unobserved heterogeneity and state dependence. Because of its dynamic nature, unobserved heterogeneity is modelled to vary over time. This allows to capture different latent states of poverty that change over time. Result indicates the existence of three unobserved types evolving over time according to their propensity to be poor. Moreover, a strong persistence in poverty especially for women, individuals living alone and ethnic minorities is found. Finally, the estimates indicate that giving social assistance tends to re…

Persistence (psychology)Change over timeEconomics and EconometricsClass (computer programming)Poverty05 social sciencesEthnic groupMarkov model01 natural sciences050906 social workSocial securityPoverty persistence older Americans latent Markov model social security programmes010104 statistics & probabilitySettore SECS-P/03 - Scienza Delle FinanzeDevelopment economicsEconomicsState dependenceDemographic economics0509 other social sciences0101 mathematics
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Short-run and long-run persistence of bad health among elderly

2019

We study the health dynamics among older Americans using ten waves of the Health and Retirement Study following a spell-approach and a regression-based approach. The former is fully non parametric synthesizing the sequences of health status into a Health Persistence Index. The latter approach relies on a Latent Markov (LM) model capturing persistence in poor health by modelling time-varying unobserved heterogeneity. Our results show that only few elders experiences persistently a poor health status. The higher values of the index are consistently observed with the main socio-demo-economic risk factors. Moreover LM model indicates the existence of three unobserved groups differing in their p…

Settore SECS-P/03 - Scienza Delle FinanzePersistent bad health health persistence index latent Markov model elderly Health and Retirement StudySettore SECS-S/05 - Statistica Sociale
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