Description: Provides comprehensive tools for analysing and characterizing
    mixed-level factorial designs arranged in blocks. Includes construction
    and validation of incidence structures, computation of C-matrices,
    evaluation of A-, D-, E-, and MV-efficiencies, checking of orthogonal
    factorial structure (OFS), diagnostics based on Hamming distance,
    discrepancy measures, B-criterion, Es^2 statistics, J2-distance and
    J2-efficiency, Phi-p optimality, and symmetry conditions for universal
    optimality. The methodological framework follows foundational work on
    factorial and mixed-level design assessment by Xu and Wu (2001) 
    <doi:10.1214/aos/1013699993>, and Gupta (1983) 
    <doi:10.1111/j.2517-6161.1983.tb01253.x>. These methods assist in selecting,
    comparing, and studying factorial block designs across a range of
    experimental situations.

Opens a 'shiny' app which supports theoretical and computational analysis of block designs for symmetrical and mixed level factorial experiments. This package includes tools to check whether a design has orthogonal factorial structure (OFS) with balance or not and is able to find the orthogonality deviation value if not having OFS. This package includes function  to evaluate efficiency factor of all factorial effects in two situations, in the first situation if the design is verified with OFS and balance then calculate the efficiencies of all factorial effects using a specific analytical procedure  and in the second situation if the design is verified with non-OFS and balance then a new general method has been developed and used to calculate efficiencies under the condition that the design should be proper and equi-replicated, See Gupta, S.C. and Mukerjee, R. (1987): "A Calculus for factorial arrangements".  Lecture Notes in Statistics. No. 59, Springer-Verlag, Berlin, New York, <doi:10.1007/978-1-4419-8730-3>. For the easy use of package, 'shiny' app is used for giving inputs and inputs validation.