Constructs confidence intervals (CIs) for the bootstrapped parameters in an object of class "boot.lmf".
1  ci.boot.lmf(x, clevel = 0.05)

x 
an object of class "boot.lmf". 
clevel 
the confidence level required. 
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.
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

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 λ, 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. 
Thomas Kvalnes
Engen, S., Saether, B.E., Kvalnes, T. and Jensen, H. 2012. Estimating fluctuating selection in agestructured populations. Journal of Evolutionary Biology, 25, 14871499.
lmf
, boot.lmf
, quantile
1 2 3 4 5 6 7 8 9 10  #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)

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