mle_gamma: Maximum Likelihood Estimation for X[1], ..., X[n] ~...

In dvmisc: Convenience Functions, Moving Window Statistics, and Graphics

Description

Performs maximization via nlminb. alpha and beta correspond to the shape and scale (not shape and rate) parameters described in GammaDist.

Usage

mle_gamma(x, alpha = NULL, beta = NULL, estimate_var = FALSE, ...)

Arguments

x	Numeric vector.
alpha	Numeric value specifying known alpha.
beta	Numeric value specifying known beta.
estimate_var	Logical value for whether to return Hessian-based variance-covariance matrix.
...	Additional arguments to pass to nlminb.

Value

List containing:

1. Numeric vector of parameter estimates.

2. Variance-covariance matrix (if estimate_var = TRUE).

3. Returned nlminb object from maximizing the log-likelihood function.

4. Akaike information criterion (AIC).

Examples

# Generate 1,000 values from Gamma(0.5, 1) and estimate alpha and beta
set.seed(123)
x <- rgamma(1000, shape = 0.5, scale = 1)
mle_gamma(x)

dvmisc documentation built on Dec. 18, 2019, 1:35 a.m.