The general Nature of Saturated Designs

08/09/2019
by   Francois Domagni, et al.
0

In a full two-level factorial experiment the design matrix is a Hadamard matrix H. The OLS estimator of the full set of parameters β ( the mean, the main effects and interactions) is given by β̂ = 1/NH^TY.Thus the estimator of each parameter except the mean is a contrast. That is H^T1_N = < b m a t r i x >. In this paper we show this result not only holds for Hadamard matrices but also holds for any saturated design matrix D in the two-level factorial experiment set-up.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/15/2023

Matrix quadratic risk of orthogonally invariant estimators for a normal mean matrix

In estimation of a normal mean matrix under the matrix quadratic loss, w...
research
11/02/2019

On The Study Of D-Optimal Saturated Designs For Mean, Main Effects and F_1-Two-Factor Interactions For 2^k-Factorial Experiments

The goal of this paper is to develop methods for the construction of sat...
research
05/29/2019

The cost-free nature of optimally tuning Tikhonov regularizers and other ordered smoothers

We consider the problem of selecting the best estimator among a family o...
research
06/21/2022

Efficiency Requires Adaptation

The majority of historical designs are a priori in nature, where a prior...
research
06/30/2020

The finiteness conjecture holds in SL(2,Z>=0)^2

Let A,B be matrices in SL(2,R) having trace greater than or equal to 2. ...
research
02/17/2020

Estimating the number and effect sizes of non-null hypotheses

We study the problem of estimating the distribution of effect sizes (the...

Please sign up or login with your details

Forgot password? Click here to reset