rng_respecting_sample: Sampling in which zero probabilities are removed

In DDD: Diversity-Dependent Diversification

Sampling in which zero probabilities are removed

Description

Sampling in which zero probabilities are removed

Usage

rng_respecting_sample(x, size, replace, prob)

Arguments

x	either a vector of one or more elements from which to choose, or a positive integer. See ‘Details.’
size	a non-negative integer giving the number of items to choose.
replace	should sampling be with replacement?
prob	a vector of probability weights for obtaining the elements of the vector being sampled.

Value

a vector of length size with elements drawn from either x or from the integers 1:x.

Note

thanks to Pedro Neves for finding this feature in base::sample

Author(s)

Richel J.C. Bilderbeek

See Also

See sample for more details

Examples

  # Number of draws
  n <- 1000
  
  # Do normal sampling
  set.seed(42)
  draws_1 <- DDD:::rng_respecting_sample(
    1:3, size = n, replace = TRUE, prob = c(1.0, 1.0, 1.0)
  )
  
  # Do a sampling with one element of probability zero
  set.seed(42)
  draws_2 <- DDD:::rng_respecting_sample(
    1:4, size = n, replace = TRUE, prob = c(1.0, 1.0, 1.0, 0.0)
  )
  testit::assert(sum(draws_2 == 4) == 0)
  testit::assert(draws_1 == draws_2)
  
  # Use base sampling will give different results,
  # as it results in different RNG values
  set.seed(42)
  draws_3 <- sample(
    1:4, size = n, replace = TRUE, prob = c(1.0, 1.0, 1.0, 0.0)
  )
  testit::assert(sum(draws_3 == 4) == 0)
  testit::assert(!all(draws_1 == draws_3))
  

DDD documentation built on July 26, 2023, 5:25 p.m.