predict_prd: Predition of assembly property by cross-validation

In BenitoJaillard/combinAna: Element clustering that best accounts for an assembly property or function

Description

Take a numeric vector and return the predicted vector computed as the arithmetic mean of all elements belonging to a same motif.

Usage

predict_prd(fct, assMotifs, mOccur, xpr,
                  opt.mean = "amean",
                  opt.mod  = "bymot",
                  opt.jack = FALSE, jack = c(2, 5)  )

Arguments

fct	a vector of numeric values (assembly properties).
assMotifs	a vector of labels of length(fct) (assembly motifs).
mOccur	a matrix of occurrence (occurrence of elements). Its first dimension equals to length(fct). Its second dimension equals to the number of elements.
xpr	a vector of labels of length(fct) (assembly experiments).
opt.mean	equal to "amean" (by default) or to "gmean".
opt.mod	equal to "bymot" (by default) or to "byelt".
opt.jack	a logical to block or switch to jackknife cross-validation.
jack	jack = c(2, 5) by default.

Details

Prediction is computed using arithmetic mean amean by motif bymot in a whole (WITHOUT taking into account species contribution). The elements belonging to a same motif are divided into jack[2] subsets of jack[1] elements. Prediction is computed by excluding jack[1] elements, of which the element to predict. If the total number of elements belonging to the motif is lower than jack[1]*jack[2], prediction is computed by Leave-One-Out (LOO).

Value

Return the arithmetic mean of a vector, as standard mean function.

BenitoJaillard/combinAna documentation built on May 9, 2019, 2:17 a.m.