Estimate temporal coefficients of selection assuming no fluctuating selection
nfs is a function which estimates the temporal covariance matrix
and the temporal mean alpha coefficients (i.e. directional
selection) under the assumption of no fluctuating selection.
nfs(At, at, npar, nyear)
a list containing the named yearly variance-covariance matrices. Sorted by year.
a list containing the named yearly vectors of the estimated selection coefficients. Sorted by year.
the number of parameters in the model for the estimates selection coefficients.
the number of years with estimates of selection.
nfs is used internally in
lmf when estimating temporal mean
coefficients of selection under the assumption of no fluctuating selection, but
given the right data can be executed as a standalone. The input to the
arguments At and at are estimated within
lmf by correctly combining
estimates of coefficients and variance-covariance within each age class and year
to a estimate for each year.
Engen et al. 2012 describe the method in details.
nfs returns a list containing the following components:
the estimated temporal covariance matrix under the assumption of no flucutating selection.
the estimated temporal mean selection coefficients under the assumption of no fluctuating selection.
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.
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#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 At and at At <- lmf.1$At at <- lmf.1$at #Estimate temporal selection coefficients under the assumption of no #fluctuating selection noflusel <- nfs(At = At, at = at, npar = 3, nyear = 7) #View output str(noflusel) noflusel
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