MLE.matching: Maximum likelihood estimator (MLE) in the generalised...

In stat.extend: Highest Density Regions and Other Functions of Distributions

Description

MLE.matching returns the maximum likelihood estimator (MLE) for the data.

Usage

MLE.matching(
  x,
  size,
  CI.method = "asymptotic",
  conf.level = 0.95,
  bootstrap.sims = 10^3
)

Arguments

x	A vector of numeric values to be used as arguments for the mass function
size	The size parameter for the generalised matching distribution (number of objects to match)
CI.method	The method used to compute the confidence interval ('asymptotic' or 'bootstrap')
conf.level	The width of the CI
bootstrap.sims	The number of bootstrap simulations used in the bootstrap confidence interval

Details

This function computes the maximum likelihood estimator (MLE) from data consisting of IID samples from the generalised matching distribution. Further details on the distribution can be found in the following paper:

Value

If all inputs are correctly specified (i.e., parameters are in allowable range) then the output will be a list of outputs for the MLE

References

O'Neill, B. (2021) A generalised matching distribution for the problem of coincidences.

Examples

X <- rmatching(20, 5, prob=.1)

# For comparison
# MASS::fitdistr(X, dmatching, start=list(prob=.5), size=5, lower=c(prob=0), upper=c(prob=1))

MLE.matching(X, 5)

stat.extend documentation built on Nov. 23, 2021, 5:06 p.m.