Optimal Row-Column Designs for Asymmetrical Factorial Experiments

Constructs and analyzes optimal row-column designs for mixed-level factorial experiments under square and rectangular field layouts. 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) . For rectangular field layouts, the package constructs designs by extracting a balanced principal block from a mixed-level block design, 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 includes repair utilities for improving disconnected or partially connected row-column designs through bounded treatment-swap searches while preserving the row-column layout structure. The package provides diagnostic tools for connectedness, orthogonal factorial structure, balance, estimability, and selected optimality criteria for row-column designs.