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pRepDesigns (version 1.2.0)

Partially Replicated (p-Rep) Designs

Description

Early generation breeding trials are to be conducted in multiple environments where it may not be possible to replicate all the lines in each environment due to scarcity of resources. For such situations, partially replicated (p-Rep) designs have wide application potential as only a proportion of the test lines are replicated at each environment. A collection of several utility functions related to p-Rep designs have been developed. Here, the package contains six functions for a complete stepwise analytical study of these designs. Five functions pRep1(), pRep2(), pRep3(), pRep4() and pRep5(), are used to generate five new series of p-Rep designs and also compute average variance factors and canonical efficiency factors of generated designs. A fourth function NCEV() is used to generate incidence matrix (N), information matrix (C), canonical efficiency factor (E) and average variance factor (V). This function is general in nature and can be used for studying the characterization properties of any block design. A construction procedure for p-Rep designs was given by Williams et al.(2011) which was tedious and time consuming. Here, in this package, five different methods have been given to generate p-Rep designs easily.

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Version

Install

install.packages('pRepDesigns')

Monthly Downloads

156

Version

1.2.0

License

GPL (>= 2)

Maintainer

Vinaykumar L.N.

Last Published

April 2nd, 2024

Functions in pRepDesigns (1.2.0)

NCEV

Incidence Matrix, Information Matrix, Canonical efficiency factor, Variance between associates and average variance
pRep4

p-rep designs with unequal block sizes
pRep1

First series of p-rep designs
pRep2

Second series of p-rep designs
pRep5

p-rep designs with equal block sizes
pRep3

Third series of p-rep designs