b_bootstrap function

b_bootstrap

Performs a Bayesian bootstrap and returns a sample of size n1 representing the posterior distribution of the statistic. Returns a vector if the statistic is one-dimensional (like for mean(...)) or a data.frame if the statistic is multi-dimensional (like for the coefficients of lm).

b_bootstrap(
  data,
  statistic,
  n1 = 1000,
  n2 = 1000,
  use_weights = FALSE,
  weight_arg = NULL,
  ...
)

Arguments

• data: The data as either a vector, matrix or data.frame.
• statistic: A function that accepts data as its first argument and if use_weights is TRUE the weights as its second argument. Function should return a numeric vector.
• n1: The size of the bootstrap sample (default = 1000).
• n2: The sample size used to calculate the statistic each bootstrap draw (default = 1000).
• use_weights: Whether the statistic function accepts a weight argument or should be calculated using resampled data (default = FALSE).
• weight_arg: If the statistic function includes a named argument for the weights this could be specified here (default = NULL).
• ...: Further arguments passed on to the statistic function.

Returns

A data frame containing bootstrap samples.

Examples

# linear function of seqence vs. response
lm_statistic <- function(data) {
  lm(sequence ~ response, data)$coef
}

# load data
data <- adaptation_level_small

# bootstrap
data_bootstrap <- b_bootstrap(data, lm_statistic, n1 = 1000, n2 = 1000)

References

https://www.sumsar.net/blog/2015/07/easy-bayesian-bootstrap-in-r/

Rubin, D. B. (1981). The Bayesian Bootstrap. The annals of statistics, 9(1), 130-134.

Author(s)

Rasmus Baath