NeuDist (version 1.0.1)

qq.plot: Generic Quantile-Quantile(Q-Q) Plot Function

Description

Generates a Q-Q (quantile–quantile) plot for any custom or built-in probability distribution. The function compares sample quantiles with theoretical quantiles computed using a user-specified quantile function.

Usage

qq.plot(sample, qfun, params, fit.line = FALSE)

Value

This function returns no value; it produces a Q-Q plot.

Arguments

sample

A numeric vector of sample observations.

qfun

A quantile function corresponding to the theoretical distribution (e.g., qnorm, qexp, or a custom quantile function).

params

A named list of distribution parameters (e.g., list(mean = 0, sd = 1) or list(alpha = 2, lambda = 1)).

fit.line

Logical; if TRUE (default), a red least-squares regression line is added to the plot. Also, displays the regression line equation and R-square value on the plot.

Details

The function is general and can be used with any continuous distribution for which a quantile function is available. It overlays both a 45° reference line and (optionally) a fitted linear regression line through the points, enabling visual assessment of model fit. Also, displays the regression line equation and R² value on the plot.

Requires user-defined function 'qfun' for the CDF of the user-defined continuous distribution.

Missing values in the sample are automatically removed with a warning.

Examples

# Example 1: Exponential distribution
set.seed(123)
x <- rexp(100, rate = 2)
qq.plot(x, qexp, list(rate = 2))

# Example 2: Customizing the fitted line
qq.plot(x, qexp, list(rate = 2),
              fit.line = TRUE)

# Example 3: Without regression line
qq.plot(x, qexp, list(rate = 2), fit.line = FALSE)

# Example 4: Display regression equation and R-square value
qq.plot(x, qexp, list(rate = 2), fit.line = TRUE)

# Example 5: For a user defined distribution
# Exponentiated Exponential Power (EEP) Distribution
#Data
x <- waiting
qq.plot(x,
      params = list(alpha=0.3407, lambda=0.6068, theta=7.6150),
      qfun = qgen.exp.power, fit.line=TRUE)