Maximum likelihood estimation of matrix exponential spatial specification on seemingly unrelated regression-spatial autoregressive model.

ABSTRACT: Spatial Seemingly unrelated regression estimation with matrix exponential specification (abbreviated as SUR-MESS(1,0)) is a new alternative when estimation of a spatial seemingly unrelated regression model with spatial autoregressive (abbreviated as SUR-SAR) has difficulty using large data. The difficulties faced are numerical iteration in obtaining parameters, theoretical complexity, and computational difficulties in calculating the Jacobian matrix so that it is not effective and efficient. With these difficulties, it is necessary to develop a new approach or model, one of which uses the Matrix Exponential Spatial Specification (MESS). The MESS specification for alternative SAR models is MESS(1,0). The existence of several properties possessed by MESS(1,0) causes this model to be better t

SUBMITTER: Marsono 

PROVIDER: S-EPMC12147878 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature