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Home  >  Volume 46 (May, 2018)

14. BAYESIAN SPATIAL HETEROSCEDASTIC AUTOREGRESSIVE MODEL [BSHAR] by Oloyede I. Volume 46 (May, 2018 Issue), pp107 –114
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BAYESIAN SPATIAL HETEROSCEDASTIC AUTOREGRESSIVE MODEL [BSHAR]

Oloyede I.

Department of Statistics, University of Ilorin.

Abstract

The study investigates the impact of spatial heteroscedastic autoregressive (SHAR) model on parameter estimations by adopting white (1980) heteroscedastic covariance matrix in Bayesian paradigm. Coordinate references of 94 cities in Nigeria were collected, the study obtained the minimum and maximum values, and these were used to generate coordinate references for the entire simulated data using uniform distribution. The study computed row-standardized spatial contiguity weights with the coordinates’ reference matrix, obtained from each sample generated withρdenoted the spatial autocorrelation term.Bias and mean squares error (MSE) criteria were adopted to evaluate the performances of the SHAR model. The study found out that asymptotically, there exist consistency and efficiency of SHAR model, the modified heteroscedastic covariance matrix (HC5) also behaved well and followed the patterns of other HC.

Keywords: SHAR, Heteroscedastic, Spatial and Bayesian inference.

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