Package: PBtDesigns 1.0.0

PBtDesigns: Partially Balanced t-Designs (PBtDesigns)

The t-designs represent a generalized class of balanced incomplete block designs in which the number of blocks in which any t-tuple of treatments (t >= 2) occur together is a constant. When the focus of an experiment lies in grading and selecting treatment subgroups, t-designs would be preferred over the conventional ones, as they have the additional advantage of t-tuple balance. t-designs can be advantageously used in identifying the best crop-livestock combination for a particular location in Integrated Farming Systems that will help in generating maximum profit. But as the number of components increases, the number of possible t-component combinations will also increase. Most often, combinations derived from specific components are only practically feasible, for example, in a specific locality, farmers may not be interested in keeping a pig or goat and hence combinations involving these may not be of any use in that locality. In such situations partially balanced t-designs with few selected combinations appearing in a constant number of blocks (while others not at all appearing) may be useful (Sayantani Karmakar, Cini Varghese, Seema Jaggi & Mohd Harun (2021)<doi:10.1080/03610918.2021.2008436>). Further, every location may not have the resources to form equally sized homogeneous blocks. Partially balanced t-designs with unequal block sizes (Damaraju Raghavarao & Bei Zhou (1998)<doi:10.1080/03610929808832657>. Sayantani Karmakar, Cini Varghese, Seema Jaggi & Mohd Harun (2022)." Partially Balanced t-designs with unequal block sizes") prove to be more suitable for such situations.This package generates three series of partially balanced t-designs namely Series 1, Series 2 and Series 3. Series 1 and Series 2 are designs having equal block sizes and with treatment structures 4(t + 1) and a prime number, respectively. Series 3 consists of designs with unequal block sizes and with treatment structure n(n-1)/2. This package is based on the function named PBtD() for generating partially balanced t-designs along with their parameters, information matrices, average variance factors and canonical efficiency factors.

Authors:Sayantani Karmakar [aut, ctb], Cini Varghese [aut, ctb], Ashutosh Dalal [aut, cre], Vinaykumar LN [aut, ctb], Seema Jaggi [aut, ctb], Mohd Harun [aut, ctb]

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# Install 'PBtDesigns' in R:
install.packages('PBtDesigns', repos = c('https://ashutoshdalal97.r-universe.dev', 'https://cloud.r-project.org'))

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On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 155 downloads 1 exports 1 dependencies

Last updated 2 years agofrom:e51e7fa58a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 17 2024
R-4.5-winOKOct 17 2024
R-4.5-linuxOKOct 17 2024
R-4.4-winOKOct 17 2024
R-4.4-macOKOct 17 2024
R-4.3-winOKOct 17 2024
R-4.3-macOKOct 17 2024

Exports:PBtD

Dependencies:MASS