SciELO - Scientific Electronic Library Online

 
vol.26 issue1Estimation of stochastic volatility models via auxiliary particles filterTabu search method for combinatorial optimization supported with wolfram mathematica software author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista de Matemática Teoría y Aplicaciones

Print version ISSN 1409-2433

Abstract

SOTO, José; INFANTE, Saba; CAMACHO, Franklin  and  AMARO, Isidro R.. Estimation of a mixed effects model using a partially observed diffusion process. Rev. Mat [online]. 2019, vol.26, n.1, pp.82-98. ISSN 1409-2433.  http://dx.doi.org/10.15517/rmta.v26i1.35527.

[22]

We consider a general mixed-effects model, where the variability of random effects of experimental individuals or units is incorporated through a stochastic differential equation. These models are useful for simultane- ously analysing data from repeated measurements taken in discrete time and with errors. A Markov chain Monte Carlo algorithm was implemented to make the statistical inference a posteriori. A diagnostic analysis was carried out on the estimated parameters to detect if the model is suitable and show its convergence, in addition to the traces and posterior densities are shown. The methodology is illustrated using simulated data.

Keywords : mixed effects models; stochastic differential equations; Markov chains; Monte Carlo algorithms.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )