```
#' Copy of boot:::ts.array
#'
#' The function `ts.array` of the `boot` package is not exported, yet we depend
#' on it. It is bad to depend on private functions of a library, so we copy it
#' here in the current version such that the `boot` package is free to change
#' it.
#'
#' @param n integer. Length of original data
#' @param n.sim The length of the simulated time series. Typically this will
#' be equal to the length of the original time series but there
#' are situations when it will be larger. One obvious situation
#' is if prediction is required. Another situation in which
#' ‘n.sim’ is larger than the original length is if ‘tseries’ is
#' a residual time series from fitting some model to the
#' original time series. In this case, ‘n.sim’ would usually be
#' the length of the original time series.
#' @param R A positive integer giving the number of bootstrap replicates
#' required.
#' @param l If ‘sim’ is ‘"fixed"’ then ‘l’ is the fixed block length used
#' in generating the replicate time series. If ‘sim’ is
#' ‘"geom"’ then ‘l’ is the mean of the geometric distribution
#' used to generate the block lengths. ‘l’ should be a positive
#' integer less than the length of ‘tseries’. This argument is
#' not required when ‘sim’ is ‘"model"’ but it is required for
#' all other simulation types.
#' @param sim The type of simulation required to generate the replicate
#' time series. The possible input values are ‘"model"’ (model
#' based resampling), ‘"fixed"’ (block resampling with fixed
#' block lengths of ‘l’), ‘"geom"’ (block resampling with block
#' lengths having a geometric distribution with mean ‘l’) or
#' ‘"scramble"’ (phase scrambling).
#' @param endcorr boolean. whether or not to apply end correction
boot_ts_array <- function (n, n.sim, R, l, sim, endcorr)
{
endpt <- if (endcorr)
n
else n - l + 1
cont <- TRUE
if (sim == "geom") {
len.tot <- rep(0, R)
lens <- NULL
while (cont) {
temp <- 1 + rgeom(R, 1/l)
temp <- pmin(temp, n.sim - len.tot)
lens <- cbind(lens, temp)
len.tot <- len.tot + temp
cont <- any(len.tot < n.sim)
}
dimnames(lens) <- NULL
nn <- ncol(lens)
st <- matrix(sample.int(endpt, nn * R, replace = TRUE),
R)
}
else {
nn <- ceiling(n.sim/l)
lens <- c(rep(l, nn - 1), 1 + (n.sim - 1)%%l)
st <- matrix(sample.int(endpt, nn * R, replace = TRUE),
R)
}
list(starts = st, lengths = lens)
}
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.