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PhD seminar talk on Tuesday, December 3, 2019 at 2pm
December 3 @ 2:00 pm - 3:30 pm
Efficient and significant empirical estimate of the multivariate regression parameters will be helpful for the policymaker to make the right decisions about sophisticated interrelated issues in the dynamic world. Since the end of the twentieth century, statisticians are going forward to develop unique working methodology for estimating and testing restricted parameters. This study reviews existing methods and suggests modified maximum likelihood estimator, modified multivariate t statistic and modified joint confidence interval to get efficient estimates for linear restricted parameters of multivariate regression with continuous responses. A Monte Carlo experiment is conducted to examine relative performance of the modified methods. The proposed methodology has been also applied to detect the numerical nexus among socioeconomic determinants, food expenditure and total monthly expenditure in “Haor” areas of Bangladesh. The study reveals that logarithm form of total monthly expenditure and food expenditure as multivariate continuous responses are significantly related to total operating land, logarithm form of family size and total monthly income considering a restriction on the parameters at different level of significance. The modified methods are found to perform significantly better than the existing methods.