Robust estimation of a spatiotemporal model with structural change

Rowena F. Bastero, Erniel B. Barrios

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)

Abstract

A spatiotemporal model is postulated and estimated using a procedure that infuses the forward search algorithm and maximum likelihood estimation into the backfitting framework. The forward search algorithm filters the effect of temporary structural change in the estimation of covariate and spatial parameters. Simulation studies illustrate capability of the method in producing robust estimates of the parameters even in the presence of structural change. The method provides good model fit even for small sample sizes in short time series data and good predictions for a wide range of lengths of contamination periods and levels of severity of contamination.

Original languageEnglish
Pages (from-to)448-468
Number of pages21
JournalCommunications in Statistics - Simulation and Computation
Volume40
Issue number3
DOIs
Publication statusPublished - Mar 2011
Externally publishedYes

Keywords

  • Backfitting
  • Forward search
  • Robust estimates
  • Spatiotemporal model
  • Structural change

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