lmf (version 1.2)

ci.boot.lmf: Confidence intervals for class "boot.lmf"

Description

Constructs confidence intervals (CIs) for the bootstrapped parameters in an object of class "boot.lmf".

Usage

ci.boot.lmf(x, clevel = 0.05)

Arguments

x

an object of class "boot.lmf".

clevel

the confidence level required.

Value

ci.boot.lmf returns a list containing the following components:

call

the matched call.

nboot

the number of bootstrap replicates generated.

what

which set of parameters which has been to bootstrapped. See ?boot.lmf for details.

clevel

the confidence level specified.

uage

the unique age classes in the data set.

nage

the number of unique age classes in the data set.

l

CI for the projection matrix.

luv

CI for $\lambda$, u and v.

sigma2.dj

CI for the demographic variance for each age class.

sigma2.d

CI for the total demographic variance

M

CI for the estimated temporal covariance matrix.

aM

CI for the estimated temporal mean coefficients of selection

sigma2.e

CI for the environmental variance

Anf

CI for the estimated temporal covariance matrix assuming no fluctuating selection.

anf

CI for the estimated temporal mean selection coefficients assuming no fluctuating selection.

Details

ci.boot.lmf construct confidence intervals (CIs) from the quantiles of the bootstrap replicates and uses the function quantile.

See Engen et al. 2012 for details on the method for estimating and bootstrapping the parameters.

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, boot.lmf, quantile

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)
#Bootstrap parameters
b.1 <- boot.lmf(object = lmf.1, nboot = 10, sig.dj = TRUE,
 what = "all", asim = "parametric")
#Generate CI
ci.boot.lmf(b.1)