MLM: Most Likely Mean of the Standard Beta Probability Density...

In betafunctions: Functions for Working with Two- And Four-Parameter Beta Probability Distributions and Psychometric Analysis of Classifications

Most Likely Mean of the Standard Beta Probability Density Distribution, Given that the Observation is Considered the Most Likely Observation of the Standard Beta Probability Density Distribution (i.e., the mode).

Description

Assuming a prior Standard (two-parameter) Beta Distribution, returns the expected mean of the distribution under the assumption that the observed value is the most likely value of the distribution.

Usage

MLM(alpha, beta, x = NULL, n = NULL)

Arguments

alpha	Observed alpha value for fitted Standard Beta Probability Density Distribution.
beta	Observed beta value for fitted Standard Beta Probability Density Distribution.
x	Observed proportion-correct outcome.
n	Test-length.

Value

The expected mean of the Standard Beta probability density distribution, for which the observed mean is the most likely value.

Examples

# Assuming a prior Standard (two-parameter) Beta distribution is fit, which
# yield an alpha parameter of 10 and a beta parameter of 8, calculate the
# true-mean most likely to have produced the observations:
MLM(a = 10, b = 8)

betafunctions documentation built on May 29, 2024, 1:13 a.m.