Modelling multi-stage processes through multivariate distributions

DOI10.1080/02664760500250586zbMath1106.62107OpenAlexW1972915510MaRDI QIDQ3426397

Fidelis Ifeanyi Ugwuowo, Ashis Sen Gupta

Publication date: 8 March 2007

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760500250586

zbMATH Keywords

semi-parametricsemi-Markovbivariate exponentialhuman resource planningmulti-stage processes

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Nonparametric hypothesis testing (62G10) Parametric hypothesis testing (62F03) Inference from stochastic processes (62M99)

Related Items (6)

Markov Systems in a General State Space ⋮ On the periodicity of non-homogeneous Markov chains and systems ⋮ \(\mathcal{G}\)-inhomogeneous Markov systems of high order ⋮ Multi-Stage Semi-Markov Models for Recovery Process ⋮ Recent developments about Marshall-Olkin bivariate distribution ⋮ Exotic Properties of Non Homogeneous Markov and Semi-Markov Systems

Cites Work

• Unnamed Item
• Simplified Models of Screening for Chronic Disease: Estimation Procedures from Mass Screening Programmes
• A semi-Markov model for a multigrade population with Poisson recruitment
• Non-homogeneous semi-Markov systems and maintainability of the state sizes
• Continuous-time stochastic models of a multigrade population
• Semi-Markovian manpower models in continuous time
• Estimation of Sojourn Time in Chronic Disease Screening Without Data on Interval Cases
• A Multivariate Exponential Distribution

This page was built for publication: Modelling multi-stage processes through multivariate distributions