atCfn {lmf}

Calculate corrected temporal mean coefficients of selection

Description

Calculate the temporal mean coefficients of selection (alpha) corrected for sampling error, i.e. the best linear predictor (BLP) of alpha.

Usage

atCfn(aM, M, At, at)

Arguments

aM

the estimated temporal mean selection coefficients.

M

the estimated temporal covariance matrix (fluctuating selection).

At

a list containing the named variance-covariance matrix for each year. Sorted by year.

at

a list containing the named vectors of the estimated selection coefficient for each year. Sorted by year.

Details

Further details are found in Engen et al. 2012.

Value

Returns a vector with the named best linear predictors for the temporal mean coefficients of selection (alpha).

Author(s)

Thomas Kvalnes

References

Engen, S., Saether, B.-E., Kvalnes, T. and Jensen, H. 2012. Estimating fluctuating selection in age-structured populations. Journal of Evolutionary Biology, 25, 1487-1499.

See Also

lmf

Examples

#Data set from Engen et al. 2012
data(sparrowdata)
#Fit model
lmf.1 <- lmf(formula = cbind(recruits, survival) ~ weight + tars,
               age = age, year = year, data = sparrowdata)
#Extract aM, M, At and at
aM <- lmf.1$aM
M <- lmf.1$M
At <- lmf.1$At
at <- lmf.1$at
#Calculate Best Linear Predictor (BLP)
atCfn(aM = aM, M = M, At = At, at = at)