boot.default: Default procedure to perform bootstrap and calculate...
In MaciejDanko/BootstrapLT: CI for pash measures

Description Usage Arguments Author(s) References Examples

Default procedure to perform bootstrap and calculate confidence intervals of pash measures.

Internal function

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boot.default(dx, x, pash.parent, N = 1000, bs.er = 0.25, jk.er = 0.1,
  pace.type = "all", shape.type = "all", q = 0.5, harmonized = TRUE,
  trace = TRUE, alpha = 0.05)

`dx`	A vector with integer counts (deaths).
`x`	Beginning of the Age/time class.
`pash.parent`	A parent `pash` object.
`N`	Number of bootstrap replicates.
`bs.er`	Maximal acceptable fraction of Bootstrap errors.
`pace.type`	Which pace measure should be returned (default "all")? Use "none" if you don't wat to return any pace measure. See `GetPace` for details.
`shape.type`	Which shape measure should be returned (default "all")? Use "none" if you don't wat to return any shape measure. See `GetShape` for details.
`q`	GetPace parameter. Quantile specification for age where q percent of the life-table population is still alive (defaults to median). See `GetPace` for details.
`harmonized`	GetShape parameter. Should the harmonized version of the shape measures be returned (default `TRUE`)? See `GetShape` for details.
`trace`	Logical indicating if to show summary of performed bootstrap.
`alpha`	Significance level.
`js.er`	Maximal acceptable fraction of JackKnife errors.

Maciej J. Danko <danko@demogr.mpg.de> <maciej.danko@gmail.com>

Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York: Chapman & Hall.

# ************************** REMOVE THIS ******************************
# Some functions will not work as they are not in the namespace
# Before integrating with pash please add "pash:::" in front of them. 
# To test them just run all functions in the bootpash.r 
# ***************************** END ***********************************
## Not run: 

#Get some data
population.size=105
obj <- Inputlx(x = australia_10y$x, lx = australia_10y$lx,nax = australia_10y$nax, nx = australia_10y$nx, last_open = TRUE)
dx <- lx2dx(round(object$lt$lx*population.size))
x <- obj$lt$x

#Calcualte confidence intervals usung bootstrap
z <- boot.default(dx = dx, x = x, pash.parent = obj, trace = TRUE)
z


## End(Not run)