Create stochastic log-likelihood with subsampling

Transforms a log-likelihood function to use only a random subsample of observations. Useful for stochastic gradient ascent on large datasets.

Usage

with_subsampling(loglike, data, subsample_size, replace = FALSE)

Arguments

loglike

Base log-likelihood function. Should accept theta and data.

data

Observations (vector, matrix, or data.frame)

subsample_size

Number of observations to sample per evaluation

replace

Sample with replacement (logical, default: FALSE)

Value

Transformed log-likelihood function

Examples

if (FALSE) { # \dontrun{
# Original likelihood uses all data
data <- rnorm(10000, mean = 5, sd = 2)

loglike <- function(theta, obs = data) {
  sum(dnorm(obs, mean = theta[1], sd = theta[2], log = TRUE))
}

# Stochastic version uses random subsample
loglike_stoch <- with_subsampling(
  loglike,
  data = data,
  subsample_size = 100
)

# Each call uses different random subsample
loglike_stoch(c(5, 2))
loglike_stoch(c(5, 2))  # Different value
} # }