نتایج جستجو برای: multivariate linear regression

تعداد نتایج: 808389  

2016
W. Liu Y. Han F. Wan F. Bretz A. J. Hayter

Simultaneous confidence bands have been shown in the statistical literature as powerful inferential tools in univariate linear regression. While the methodology of simultaneous confidence bands for univariate linear regression has been extensively researched and well developed, no published work seems available for multivariate linear regression. This paper fills this gap by studying one partic...

2005
L. Prchal

Abstract. The aim of this contribution is to present a new, however rapidly developing domain of statistics – functional data analysis (FDA). A particular problem of extending multivariate regression to the functional setting is discussed. First of all, two real data sets and connected problems are presented. Multivariate regression is briefly recalled focusing mainly on the case of strongly co...

Jabbari, A., Yousefieh, M. ,

In this study, the temperature in friction stir welding of duplex stainless steel has been investigated. At first, temperature estimation was modeled and estimated at different distances from the center of the stir zone by the multivariate Lagrangian function. Then, the linear extrapolation method and multiple linear regression method were used to estimate the temperature outside the range and ...

Jabbari, A., Yousefieh, M. ,

In this study, the temperature in friction stir welding of duplex stainless steel has been investigated. At first, temperature estimation was modeled and estimated at different distances from the center of the stir zone by the multivariate Lagrangian function. Then, the linear extrapolation method and multiple linear regression method were used to estimate the temperature outside the range and ...

Journal: :Communications for Statistical Applications and Methods 2002

Journal: :Communications for Statistical Applications and Methods 2020

Journal: :Journal of Computational and Graphical Statistics 2021

We develop a new method to fit the multivariate response linear regression model that exploits parametric link between coefficient matrix and error covariance matrix. Specifically, we assume correlations entries in random vector are proportional cosines of angles their corresponding columns, so as angle two columns decreases, correlation errors increases. highlight models under which this param...

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