qBetaMS: Quantile Containing Specific Proportion of the Distribution,...

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

Quantile Containing Specific Proportion of the Distribution, Given a Specific Probability of the Beta Probability Density Distribution with Specific Mean and Variance.

Description

Calculates the quantile corresponding to a specific probability of some observation falling within the [0, x] (lt = TRUE) or [x, 1] (lt = FALSE) interval under the Standard Beta probability density distribution with defined mean and variance or standard deviation.

Usage

qBetaMS(p, mean, variance = NULL, sd = NULL, lower.tail = TRUE, l = 0, u = 1)

Arguments

p	A value of probability marking the point of the Y-axis to correspond to the X-axis.
mean	The mean of the target Standard Beta probability density distribution.
variance	The variance of the target Standard Beta probability density distribution.
sd	The standard deviation of the target Standard Beta probability density distribution.
lower.tail	Logical. Specifies which end of the tail for which to calculate quantile. Default is TRUE (meaning, find q for lower tail.)
l	The lower-bound location parameter. Default set to 0 (the standard Beta distribution).
u	The upper-bound location parameter. Default set to 1 (the standard Beta distribution).

Value

A numeric value representing the quantile for which the specified proportion of observations fall within.

Examples

# To compute the quantile at a specific point (e.g., 0.5) along the Standard
# (two-parameter) Probability Density Distribution with mean of 0.6 and variance of 0.04:
qBetaMS(p = 0.5, mean = 0.6, variance = 0.04)

# To compute the quantile at a specific points(e.g., 0.5) along the four-
# parameter Beta distribution with a mean of 60, variance of 400, and lower-
# bound of 0 and upper-bound of 100:
qBetaMS(p = 0.5, mean = 60, variance = 400, l = 0, u = 100)

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