mle_gaussian_dist: Gaussian MLE parameters and Model selection

In ssarda/genomeutils: Utilities for Genome Analysis

Description

This function accepts a vector with all values of a given unknown distribution It estimates the maximum likelihood parameters by fitting a guassian distribution over it. General-purpose optimization to estimate parameters is based on Nelder–Mead algorithm The Akaike Information Criterion is also output to enable downstream model selection

Usage

mle_gaussian_dist(X, start_mu, start_sigma)

Arguments

X	A Vector of values.
start_mu	Initial value to begin optimization at for mean of gaussian distribution
start_sigma	Initial value to begin optimization at for standard deviation of gaussian distribution

Value

A vector containing the optimized MLE mean and standard deviation as well as the log likelihood and AIC to enable downstream model selection

ssarda/genomeutils documentation built on May 30, 2019, 8:42 a.m.