pesekbaker | R Documentation |
Function to compute the Pesek-Baker index (Pesek, J. and R.J. Baker., 1969).
pesekbaker(
dfr,
geno,
G.cov,
P.cov,
vars = NULL,
dgg = NULL,
units = c("sdu", "actual"),
sf = 0.1
)
dfr |
The name of the data frame with the values for each genotype with each variable. |
geno |
The name of the column in |
G.cov |
Genotypic covariance matrix. |
P.cov |
Phenotypic covariance matrix. |
vars |
The names of the columns for the variables. The default are all the column names
in |
dgg |
Desired genetic gains. The default is one standard deviation for each variable. |
units |
Units for dgg, |
sf |
Selected fraction. The default is 0.1. |
The Pesek-Baker is an index where relative economic weights have been replaced
by desired gains.
If dgg
is not specified, the desired genetic gains are set to one
standard deviation for each variable. dgg
can be specified in actual units
(units = "actual"
) or in standard deviations (units = "sdu"
),
defaults to "sdu"
. For example, if you have a variable which is expressed
in kilograms with a standard deviation of 5 kilograms, typing dgg = 2
means a desired genetic gain of 2 standard deviations that corresponds to 10 kilograms.
If you type dgg = 2
and units = "actual"
then this means a desired
genetic gain of 2 kilograms. If dgg = NULL
then the desired genetic gains
will be one standard deviation, no matter if units
is set as "actual"
or "sdu"
.
It returns:
$Desired.Genetic.Gains
, the desired genetic gains in actual units,
$Standard.Deviations
, the estimated genotypic standard deviations,
$Index.Coefficients
, the index coefficients,
$Response.to.Selection
, the response to selection,
$Std.Response.to.Selection
, the standardized response to selection, and
$Pesek.Baker.Index
, a data frame with the genotypic means for each variable,
the Pesek-Baker index, and the rank for each genotype according to the index.
Raul Eyzaguirre.
Pesek, J. and R.J. Baker.(1969). Desired improvement in relation to selection indices. Can. J. Plant. Sci. 9:803-804.
vars <- c("rytha", "bc", "dm", "star", "nocr")
output <- ecm(spg, vars, "geno", "loc", "rep")
colnames(output$blups) <- gsub('blup.', '', colnames(output$blups))
pesekbaker(output$blups, 'geno', output$G.cov, output$P.cov)
# More weight on bc and dm, less on star and nocr
dgg <- c(1, 1.5, 1.5, 0.8, 0.8)
pesekbaker(output$blups, 'geno', output$G.cov, output$P.cov, vars, dgg)
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