64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Non-Normal Estimation of Multiple Spatial Patterns of Disease using Multivariate Skews Normal Process

Author

AK
Kassahun Ayalew

Co-author

  • S
    Samuel Manda
  • B
    Bo Cai

Conference

64th ISI World Statistics Congress - Ottawa, Canada

Format: CPS Abstract

Session: CPS 10 - Disease and mortality modelling

Monday 17 July 8:30 a.m. - 9:40 a.m. (Canada/Eastern)

Abstract

Multivariate conditional autoregressive models based on the Gaussian are commonly applied in the analysis of multivariate spatial data. However, the modelled data could be highly tailed and skewed. We present, as an alternative, a multivariate skew-normal distribution in the analysis of multiple non-Gaussian spatial data. The estimation of the spatial patterns is fully Bayesian. Simulations and an application to estimate district HIV rates in South Africa are used for illustrating the capabilities of the proposed non-Gaussain approach to the analysis of multivariate skewed data.