HadamardOCDs

Construct Hadamard matrix H_k = (1, h_1 , h_2,..., h_k-1) where k is the block size of the required design. Then superimpose each columns of H_k leaving the first column which is in natural order separately into the N matrix to get the W matrices. The maximum number of W matrices will be k-1.

We have designed this package to address experimental scenarios involving multiple covariates. It focuses on construction of Optimal Covariate Designs (OCDs), checking space filling property of the developed design. The primary objective of the package is to generate OCDs using four methods viz., M array method, Juxtapose method, Orthogonal Integer Array and Hadamard method. The package also evaluates space filling properties of both the base design and OCDs using the MaxPro criterion, providing a meaningful basis for comparison. In addition, it includes tool to visualize the spread offered by the design points in the form of scatterplot, which help users to assess distribution and coverage of design points.

Ashutosh Dalal

SFOCDs

Space Filling Optimal Covariate Designs

Neethu RS

Cini Varghese

Mohd Harun

Anindita Datta

HadamardOCDs function

<dl><dt>design</dt>
<dd>Input a design in matrix format and block size k is multiple of 4.</dd></dl>

Arguments

Neethu RS
Cini Varghese
Mohd Harun
Anindita Datta
Ashutosh Dalal

Author

Hadamard Method for Optimal Covariate Designs (OCDs) — HadamardOCDs

<dl>

<dt>design</dt>
<dd>Input a design in matrix format and block size k is multiple of 4.</dd>

</dl>

HadamardOCDs: Hadamard Method for Optimal Covariate Designs (OCDs)

Description

Usage

Value

Arguments

Author

References

Examples