boot_pb: Parametric Bootstrap

In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics

Description

Generates B number of parametric bootstrap resamples from the original sample data. Data is generated from a multivariate normal distribution using the estimated variance-covariance matrix and mean vector.

Usage

boot_pb(n, Sigma, mu, B = 2000)

Arguments

n	Sample size.
Sigma	Estimated variance-covariance matrix from the original sample data.
mu	Estimated mean vector from the original sample data.
B	Number of bootstrap resamples.

Value

Returns a list of parametric bootstrap resamples.

Author(s)

Ivan Jacob Agaloos Pesigan

See Also

Other bootstrap functions: boot_fit(), boot_lav(), boot_nb(), boot_pb_med_simple(), boot_pb_vm()

Examples

B <- 5
Sigma <- matrix(
  data = c(
    225, 112.50, 56.25,
    112.5, 225, 112.5,
    56.25, 112.50, 225
  ),
  ncol = 3
)
mu <- c(100, 100, 100)
data <- gendat_mvn(
  n = 100,
  Sigma = Sigma,
  mu = mu
)
n <- nrow(data)
est_Sigma <- cov(data)
est_mu <- colMeans(data)
boot_pb_resamples <- boot_pb(n = n, Sigma = est_Sigma, mu = est_mu, B = B)

jeksterslabds/jeksterslabRds documentation built on July 16, 2020, 3:41 p.m.