Optimality regions for designs in multiple linear regression models with correlated random coefficients

11/13/2019
by   Ulrike Graßhoff, et al.
0

This paper studies optimal designs for linear regression models with correlated effects for single responses. We introduce the concept of rhombic design to reduce the computational complexity and find a semi-algebraic description for the D-optimality of a rhombic design via the Kiefer-Wolfowitz equivalence theorem. Subsequently, we show that the structure of an optimal rhombic design depends directly on the correlation structure of the random coefficients.

READ FULL TEXT
research
08/12/2018

Various Optimality Criteria for the Prediction of Individual Response Curves

We consider optimal designs for the Kiefer cirteria, which include the E...
research
04/04/2021

D-optimal designs for the Mitscherlich non-linear regression function

Mitscherlich's function is a well-known three-parameter non-linear regre...
research
01/08/2019

The semi-algebraic geometry of optimal designs for the Bradley-Terry model

Optimal design theory for nonlinear regression studies local optimality ...
research
04/30/2021

Explanation of multicollinearity using the decomposition theorem of ordinary linear regression models

In a multiple linear regression model, the algebraic formula of the deco...
research
07/05/2023

D-optimal Subsampling Design for Massive Data Linear Regression

Data reduction is a fundamental challenge of modern technology, where cl...
research
06/21/2023

Explaining human body responses in random vibration: Effect of motion direction, sitting posture, and anthropometry

This study investigates the effects of anthropometric attributes, biolog...
research
07/26/2018

Optimal Designs in Multiple Group Random Coefficient Regression Models

The subject of this work is multiple group random coefficients regressio...

Please sign up or login with your details

Forgot password? Click here to reset