MFRCD: Optimal Row-Column Designs for Asymmetrical Factorial
Experiments
Constructs and analyzes optimal row-column designs for mixed-level
factorial experiments under two field situations like square field layouts,
where the number of rows and columns are equal, and rectangular field layouts,
where one blocking direction is determined by a selected block size.
For square field layouts, the package implements direct common-factor
constructions by first forming two component treatment arrays, one for
each factor or super-factor, and then combining them through a symbolic
cell-wise product following Gopinath, Parsad and Mandal (2018)
<doi:10.1080/03610926.2017.1376091>. For rectangular field layouts, the package constructs
designs by extracting a balanced principal block from a mixed-level block
design derived from r package mixedfact, treating it as the principal column, taking the
complete treatment set as the principal row, and generating the full row-column
design by cyclic modular development. The package also provides diagnostic
tools for connectedness, orthogonal factorial structure, balance, estimability,
A-, D-, and E-efficiency, E-optimality, and MV-optimality criterion values.
These designs are practically useful in agricultural, industrial, and biological
experiments where treatments have factorial structure and heterogeneity must be
controlled simultaneously in two directions.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=MFRCD
to link to this page.