knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 4.5, fig.align = "center" ) options(tibble.print_min = 6, tibble.print_max = 6) modern_r <- getRversion() >= "4.1.0"
The package AcceptReject
provides the function qqplot.accept_reject()
which allows us to construct quantile-quantile plots to assess the goodness of fit of a probability distribution to a data sample. Similar to the function plot.accept_reject()
, the function qqplot.accept_reject()
is a generic function that accepts an object of class accept_reject as an argument, easily constructing the plot of theoretical quantiles of f against the sample quantiles (observed quantiles).
This function works efficiently, so that in large samples, the points are optimized to generate a more efficient plot, utilizing the scattermore
library in R
.
## S3 method for class 'accept_reject' qqplot( x, alpha = 0.5, color_points = "#F890C2", color_line = "#BB9FC9", size_points = 1, size_line = 1, ... )
x
: Object of the class accept_reject returned by the function accept_reject()
.alpha
: Transparency of the points and reference line representing where the quantiles should be (theoretical quantiles).color_points
: Color of the points (default is "#F890C2"
).color_line
: Color of the reference line (detault is "#BB9FC9"
).size_points
: Size of the points (default is 1
).size_line
: Thickness of the reference line (default is 1
)....
: Additional arguments for the quantile()
function. For instance, it's possible to change the algorithm type for quantile calculation.library(AcceptReject) library(cowplot) x <- accept_reject( n = 2000L, f = dbinom, continuous = FALSE, args_f = list(size = 5, prob = 0.5), xlim = c(0, 5) ) a <- plot(x) b <- qqplot(x) plot_grid(a, b, ncol = 2)
# For n = 1000 y <- accept_reject( n = 1000L, f = dbeta, continuous = TRUE, args_f = list(shape1 = 2, shape2 = 2), xlim = c(0, 1) ) # For many points (scattermore is used): z <- accept_reject( n = 11e3, f = dbeta, continuous = TRUE, args_f = list(shape1 = 2, shape2 = 2), xlim = c(0, 1) ) # Gráficos a <- plot(y) b <- qqplot(y) c <- plot(z) d <- qqplot(z) plot_grid(a, b, ncol = 2) plot_grid(c, d, ncol = 2)
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