The Bayesian methodology is used in this paper to derive the prediction distribution of future responses matrix for multivariate simple linear model with matrix-T error. Results reveal that the prediction distribution of future responses matrix is a matrix-T distribution with appropriate location, scale and shape parameters. The prediction distribution depends on the realized responses only through the sample regression matrix and the sample residual sum of squares and products matrix. The study model is robust and the Bayesian method is competitive with other statistical methods in the field of predictive inference. Some applications of predictive inference have also been illustrated.Azizur Rahmanhttp://www.pspchv.com/content_1_PJTAS_2.htm
ABSTRACT This research aims to study: the use of matrices in predicting the future value of a simpl...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
Both Bayesian and classical approaches are used to derive the prediction distribution of a set of fu...
[Abstract]: This thesis investigates the prediction distributions of future response(s), conditi...
AbstractThe predictive distributions of the future responses and regression matrix under the multiva...
[Abstract]: Prediction distribution is a basis for predictive inferences applied in many real world ...
[Abstract]: This thesis investigates the prediction distributions of future response(s), conditi...
The prediction distributions of the future responses, conditional on the observed responses, from th...
Baysian inference is considered for the precision matrix of the multivariate regression model with d...
It is becoming increasingly important to learn from a partially-observed random matrix and predict i...
This paper proposes predictive inference for the multiple regression model with independent normal e...
In recent years, with widely accesses to powerful computers and development of new computing methods...
In recent years, with widely accesses to powerful computers and development of new computing methods...
In recent years, with widely accesses to powerful computers and development of new computing methods...
ABSTRACT This research aims to study: the use of matrices in predicting the future value of a simpl...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
Both Bayesian and classical approaches are used to derive the prediction distribution of a set of fu...
[Abstract]: This thesis investigates the prediction distributions of future response(s), conditi...
AbstractThe predictive distributions of the future responses and regression matrix under the multiva...
[Abstract]: Prediction distribution is a basis for predictive inferences applied in many real world ...
[Abstract]: This thesis investigates the prediction distributions of future response(s), conditi...
The prediction distributions of the future responses, conditional on the observed responses, from th...
Baysian inference is considered for the precision matrix of the multivariate regression model with d...
It is becoming increasingly important to learn from a partially-observed random matrix and predict i...
This paper proposes predictive inference for the multiple regression model with independent normal e...
In recent years, with widely accesses to powerful computers and development of new computing methods...
In recent years, with widely accesses to powerful computers and development of new computing methods...
In recent years, with widely accesses to powerful computers and development of new computing methods...
ABSTRACT This research aims to study: the use of matrices in predicting the future value of a simpl...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...
The multivariate mixed linear model or multivariate components of variance model with equal replicat...