lmf (version 1.2)

summary.boot.lmf: Summarizing bootstraps of lmf fits

Description

summary method for class "boot.lmf".

Usage

"summary"(object, ret.bootstraps = FALSE, ...) "print"(x, digits = max(3, getOption("digits") - 3), signif.stars = getOption("show.signif.stars"), ...)

Arguments

object

an object of class "boot.lmf". empty

ret.bootstraps

logical. If TRUE the bootstrap replicates are returned in the output. empty

x

an object of class "summary.boot.lmf". empty

digits

the number of significant digits to use when printing. empty

signif.stars

logical. If TRUE, 'significance stars' are printed for each coefficient.

...

further arguments passed to or from other methods.

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 $(\lambda)$, 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 variance-covariance matrix (M).

Mboot.mean

the bootstrap mean temporal variance-covariance matrix.

Mbias

the bootstrap bias of the components of the temporal variance-covariance matrix.

Mboot.sd

the boostrap standard deviation of the components of the temporal variance-covariance 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 variance-covariance matrix under the assumtion of no fluctuating selection.

Anfboot.mean

the bootstrap mean temporal variance-covariance matrix under the assumption of no fluctuating selection.

Anfbias

the bootstrap bias of the components of the temporal variance-covariance matrix under the assumption of no fluctuating selection.

Anfboot.sd

the boostrap standard deviation of the components of the temporal variance-covariance 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 p-values. All under the specified null hypothesis H0exp and the assumption of fluctuating selection (Hexp = "fs").

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 p-values. All under the specified null hypothesis H0exp and the assumption of no fluctuating selection (Hexp = "nfs").

coefficients.aH0Mnfboot

the estimated temporal components of the variance-covariance matrix, with bootstrapped standard errors, number of successes with regard to the null hypothesis and associated p-values. All under the specified null hypothesis H0exp and the assumption of directional selection (Hexp = "ds").

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 variance-covariance 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 variance-covariance 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 variance-covariance matrix (M). The first columns contain coefficients (where (Intercept) (a(M)) is the first coefficient), and subsequent columns contain the components of the variance-covariance 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 variance-covariance 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 variance-covariance matrix (where (Intercept)-(Intercept) (At(M=0)) is the first component (from the diagonal) of the matrix)

H0aMboot

the bootstrap replicates of aM under the specified null hypothesis H0exp and the assumption of fluctuating selection (Hexp = "fs").

H0anfboot

the bootstrap replicates of anf under the specified null hypothesis H0exp and the assumption of no fluctuating selection (Hexp = "nfs").

H0atnfboot

the bootstrap replicates of at under the specified null hypothesis H0exp and the assumption of directional selection (Hexp = "ds"). These bootstrap replicates are used to generate H0Mnfboot.

H0Mnfboot

the bootstrap replicates of M under the specified null hypothesis H0exp and the assumption of directional selection (Hexp = "ds").

Details

summary.boot.lmf formats bootstrap replicates in a user-friendly way, and formats the temporal coefficients and variance-covariance matrix into easily read tables for hypothesis tests.

See Also

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