Summarizing bootstraps of lmf fits
Description
summary
method for class "boot.lmf".
Usage
1 2 3 4 5 
Arguments
object 
an object of class "boot.lmf". empty 
ret.bootstraps 
logical. If 
x 
an object of class "summary.boot.lmf". empty 
digits 
the number of significant digits to use when printing. empty 
signif.stars 
logical. If 
... 
further arguments passed to or from other methods. 
Details
summary.boot.lmf
formats bootstrap replicates in a userfriendly way,
and formats the temporal coefficients and variancecovariance matrix into
easily read tables for hypothesis tests.
Value
The function summary.boot.lmf
computes and returns a list of summary
statistics of the bootstrap replicates of a fitted lmf
model given
in object
.
An object of class "summary.boot.lmf" is a list containing at most the following components:
call 
the matched call. 
nboot 
the number of bootstrap replicates generated. 
lest 
the estimated projection matrix. 
lboot.mean 
the bootstrap mean projection matrix. 
lbias 
the bootstrap bias of the components of the projection matrix. 
lboot.sd 
the boostrap standard deviation of the components of the projection matrix. 
luv 
the estimate, bootstrap mean, bias and standard deviation of the deterministic multiplicative growth rate of the population (λ), the stable age distribution (u) and the reproductive values (v). 
sigma2.e 
the estimate, bootstrap mean, bias and standard deviation of the environmental variance of the population. 
sigma2.dd 
the estimate, bootstrap mean, bias and standard deviation of the demographic variances (by age class and in total). 
aM 
the estimate, bootstrap mean, bias and standard deviation of the estimated temporal mean selection coefficients. 
Mest 
the estimated temporal variancecovariance matrix (M). 
Mboot.mean 
the bootstrap mean temporal variancecovariance matrix. 
Mbias 
the bootstrap bias of the components of the temporal variancecovariance matrix. 
Mboot.sd 
the boostrap standard deviation of the components of the temporal variancecovariance matrix. 
anf 
the estimate, bootstrap mean, bias and standard deviation of the estimated temporal mean selection coefficients under the assumption of no fluctuating selection. 
Anfest 
the estimated temporal variancecovariance matrix under the assumtion of no fluctuating selection. 
Anfboot.mean 
the bootstrap mean temporal variancecovariance matrix under the assumption of no fluctuating selection. 
Anfbias 
the bootstrap bias of the components of the temporal variancecovariance matrix under the assumption of no fluctuating selection. 
Anfboot.sd 
the boostrap standard deviation of the components of the temporal variancecovariance matrix under the assumption of no fluctuating selection. 
coefficients.aH0aMboot 
the estimated temporal mean selection
coefficients, with bootstrapped standard errors, number of
successes with regard to the null hypothesis and associated pvalues. All
under the specified null hypothesis 
coefficients.aH0anfboot 
the estimated temporal mean selection
coefficients under the assumtion of no fluctuating selection, with
bootstrapped standard errors, number of successes with regard to the null
hypothesis and associated pvalues. All under the specified null hypothesis

coefficients.aH0Mnfboot 
the estimated temporal components of the
variancecovariance matrix, with bootstrapped standard errors, number of
successes with regard to the null hypothesis and associated pvalues. All
under the specified null hypothesis 
lluvboot 
the bootstrap replicates of the projection matrix (columns f (fecundity) and s (survial)), lambda, the stable age distribution (u) and the reproductive values (v). Numbers in the column names indicate age class. 
deboot 
the bootstrap replicates of the demographic and environmental variances. Numbers in the column names indicate age class. 
atAboot 
the bootstrap replicates of the yearly coefficients of selection (at) and variancecovariance matrix (At). The first column indicate boostrap number and the second the boostrapped year. The subsequent columns contain coefficients (where (Intercept) (at) is the first coefficient), and components of the variancecovariance matrix (where (Intercept)(Intercept) (At) is the first component (from the diagonal) of the matrix) 
aMMboot 
the bootstrap replicates of the temporal mean coefficients of selection (aM) and variancecovariance matrix (M). The first columns contain coefficients (where (Intercept) (a(M)) is the first coefficient), and subsequent columns contain the components of the variancecovariance matrix (where (Intercept)(Intercept) (M) is the first component (from the diagonal) of the matrix) 
atCboot 
the bootstrap replicates of the yearly coefficients of selection (atC) corrected for sampling error. The first column indicate boostrap number, the second the boostrapped year and the subsequent columns contain the boostrapped coefficients. 
anfAboot 
the bootstrap replicates of the temporal mean coefficients of selection (anf) and variancecovariance matrix under the assumption of no fluctuating selection. The first columns contain coefficients (where (Intercept) (a(M=0)) is the first coefficient), and subsequent columns contain the components of the variancecovariance matrix (where (Intercept)(Intercept) (At(M=0)) is the first component (from the diagonal) of the matrix) 
H0aMboot 
the bootstrap replicates of 
H0anfboot 
the bootstrap replicates of 
H0atnfboot 
the bootstrap replicates of 
H0Mnfboot 
the bootstrap replicates of 
Author(s)
Thomas Kvalnes
See Also
lmf
, summary
, boot.lmf
Examples
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")
#Summary
summary(b.1)
