to_k_lambda_weibull: Parameter Conversion for Weibull Distribution

In mixR: Finite Mixture Modeling for Raw and Binned Data

Description

The function to_k_lambda_weibull converts the mean and standard deviation to the shape and scale for the Weibull distributions.

Usage

to_k_lambda_weibull(mu, sd)

Arguments

mu	a numeric vector representing the means of Weibull distributions
sd	a numeric vector representing the standard deviations of Weibull distributions. mu and sd should have the same length.

Details

The purpose of this function is to convert the parameterization of Weibull distribution in the form of mean and standard deviation to the form of shape and scale. It can be used for specifying the initial values for the EM algorithm when the first-hand initial values are in the form of mean and standard deviation from K-means clustering algorithm.

Value

a list of two items

k	a vector of the shapes of Weibull distributions
lambda	a vector of the scales of Weibull distributions

See Also

to_mu_sd_weibull

Examples

to_k_lambda_weibull(2, 1)
to_k_lambda_weibull(c(2, 5), c(1, 0.7))

mixR documentation built on June 1, 2021, 5:07 p.m.