| QQplotgg {mistr} | R Documentation | 
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,
  ...
)
## Default S3 method:
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 class '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. | 
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.
Value
ggplot object.
Examples
# 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))