mistr (version 0.0.2)

QQplotgg: Implementation of Quantile-Quantile Plot with ggplot2

Description

QQplotgg is a generic function that produces QQ plot of two datasets, distribution and dataset or two distributions.

Usage

QQplotgg(d1, d2, line = TRUE, col = "#F9D607", line_col = "#f28df9",
  xlab = deparse(substitute(d1)), ylab, main = "Q-Q plot", alpha,
  lwd = 1, ...)
# S3 method for default
QQplotgg(d1, d2, line = TRUE, col = "#F9D607",
  line_col = "#f28df9", xlab = deparse(substitute(d1)),
  ylab = deparse(substitute(d2)), main = "Q-Q plot", alpha = 0.5,
  lwd = 1, ...)
# S3 method for dist
QQplotgg(d1, d2, line = TRUE, col = "#F9D607",
  line_col = "#f28df9", xlab = deparse(substitute(d1)), ylab = ylabe,
  main = "Q-Q plot", alpha = 0.7, lwd = 1, CI = re,
  CI_alpha = 0.4, CI_col = line_col, conf = 0.95, n = 100, ...)
QQnormgg(d2, xlab = "Standard Normal", ylab = deparse(substitute(d2)),
  ...)

Arguments

d1

distribution object or dataset.

d2

distribution object or dataset.

line

if qqline should be included, default: TRUE.

col

color of points, default: '#F9D607'.

line_col

color of qqline, default: '#f28df9'.

xlab

xlab, default: deparse(substitute(d1)).

ylab

ylab. default: deparse(substitute(d2)).

main

title, default: 'Q-Q plot'.

alpha

alpha of points, default: 0.7.

lwd

lwd of qqline, default: 1.

...

further arguments to be passed.

CI

if confidence bound should be included.

CI_alpha

alpha of confidence bound, default: 0.4.

CI_col

color of confidence bound , default: line_col.

conf

confidence level for confidence bound, default: 0.95.

n

number of points at which quantile functions are evaluated if two distributions are compared, default: 100.

Value

ggplot object.

Details

QQplotgg is able to compare any combination of dataset and distributions.

QQnormgg is a wrapper around QQplotgg, where d1 is set to normdist().

If quantiles of a continuous distribution are compared with a sample, a confidence bound for data is offered. This confidence "envelope" is based on the asymptotic results of the order statistics. For more details see https://en.wikipedia.org/wiki/Order_statistic.

Examples

# NOT RUN {
# sample vs sample
QQplotgg(r(normdist(), 10000), r(tdist(df = 4), 10000))

# distribution vs sample
QQplotgg(normdist(), r(tdist(df = 4), 10000))

# distribution vs distribution
QQplotgg(normdist(), tdist(df = 4))
# }