bootstrap {CIS.DGLM}

Bootstrap

Description

This function implements a custom bootstrapping procedure that utilizes bootstrapping to estimate mean and SD of stress between two environment states (A and B).

Usage

bootstrap(
  dataset,
  n.boot = 10^5,
  variables,
  stress_variable,
  alpha = 0.05,
  ran.seed = 12345
)

Arguments

dataset

Data set to be utilized.

n.boot

Number of bootstraps to perform. Defaults to 10^5.

variables

List of variables from mean and variance models in DGLM.

stress_variable

Name of the variable with the stress values.

alpha

Significance level by which to determine the confidence intervals for the bootstrap estimates. Defaults to 0.05, thus creating the 95 percent confidence intervals.

ran.seed

Random seed value for generating different random bootstrap samples.]

Value

Lists with confidence intervals for the bootstrap estimations for average stress in As and Bs of variables in mean model and confidence intervals for the bootstrap estimations of standard deviation of stress in As and Bs of variables in variance model.

Examples

test.data <- simu.inter.dat.interboth(n.rep = 3, n.obs.per.rep = 15, ran.seed = 1)
variables <- colnames(test.data[-1])
bootstrap(test.data, n.boot=100,variables, 'stress')
unlink(c('bootstrap mean A stress.txt','bootstrap mean B stress.txt',
'bootstrap sd A stress.txt', 'bootstrap sd B stress.txt'))