Now showing items 1-3 of 3

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    A test statistic for selection of multivariate linear regression models 

    Srisuda Boonyim; Jirawan Jitthavech (National Institute of Development Administration, 2015)

    In this study, a test statistic used to select a multivariate linear regression model based on Mallows’s Cp with the same rationale as the SCp criterion from the system of equations Vichit Lorchirachoonkul and Jirawan Jitthavech (2012: 2386- 2394) proposed. The D statistic, which is the difference between the modified Cp statistics in the reduced model and in the full model, approximates to a standard normal distribution.
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    Corrected score estimators in multivariate regression models with heteroscedastic measurement errors 

    Wannaporn Junthopas; Jirawan Jitthavech (National Institute of Development Administration, 2016)

    In this study, the knowledge of parameter estimation theory based on the corrected score (CS) approach is extended in a linear multivariate multiple regression model with heteroscedastic measurement errors (HME) and an unknown HME variance. The heteroscedasticity of the HME variance is assumed to be capable of being grouped into similar patterns where the sample of observations are assembled into several sub-samples with the property that the variances of the measurement error (ME) are homoscedastic within a group but heteroscedastic between ...
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    Response surface methodology using an optimization technique 

    Chanta Wongoutong; Jirawan Jitthavech (National Institute of Development Administration, 2016)

    Response surface methodology (RSM) is techniques combine both of experimental designs and statistical techniques for empirical model building and optimization. The experimental design is considered by the objective is to optimize one or more response variables influenced by several independent variables. However, in real situation, we may not be able to identify the true model and so an approximated model, usually a central composite design for building a second-order polynomial model, this design is popular in RSM.