Pdqr methods for base plotting functions
## S3 method for class 'p' plot(x, y = NULL, n_extra_grid = 1001, ...) ## S3 method for class 'd' plot(x, y = NULL, n_extra_grid = 1001, ...) ## S3 method for class 'q' plot(x, y = NULL, n_extra_grid = 1001, ...) ## S3 method for class 'r' plot(x, y = NULL, n_sample = 1000, ...) ## S3 method for class 'p' lines(x, n_extra_grid = 1001, ...) ## S3 method for class 'd' lines(x, n_extra_grid = 1001, ...) ## S3 method for class 'q' lines(x, n_extra_grid = 1001, ...)
x |
Pdqr-function to plot. |
y |
Argument for compatibility with |
n_extra_grid |
Number of extra grid points at which to evaluate
pdqr-function (see Details). Supply |
... |
Other arguments for |
n_sample |
Size of a sample to be generated for plotting histogram in case of an r-function. |
Main idea of plotting pdqr-functions is to use plotting mechanisms for appropriate numerical data.
Plotting of type discrete functions:
P-functions are plotted as step-line with jumps at points of "x" column of "x_tbl" metadata.
D-functions are plotted with vertical lines at points of "x" column of "x_tbl" with height equal to values from "prob" column.
Q-functions are plotted as step-line with jumps at points of "cumprob" column of "x_tbl".
R-functions are plotted by generating sample of size n_sample and calling
hist() function.
Plotting of type continuous functions:
P-functions are plotted in piecewise-linear fashion at their values on
compound grid: sorted union of "x" column from "x_tbl" metadata and sequence
of length n_extra_grid consisting from equidistant points between edges of
support. Here extra grid is needed to show curvature of lines between "x"
points from "x_tbl" (see Examples).
D-functions are plotted in the same way as p-functions.
Q-functions are plotted similarly as p- and d-functions but grid consists
from union of "cumprob" column of "x_tbl" metadata and equidistant grid of
length n_extra_grid from 0 to 1.
R-functions are plotted the same way as type "discrete" ones: as histogram
of generated sample of size n_sample.
Output of invisible() without arguments, i.e.
NULL without printing.
Other pdqr methods for generic functions:
methods-group-generic,
methods-print
d_norm_1 <- as_d(dnorm) d_norm_2 <- as_d(dnorm, mean = 1) plot(d_norm_1) lines(d_norm_2, col = "red") # Usage of `n_extra_grid` is important in case of "continuous" p- and # q-functions simple_p <- new_p(data.frame(x = c(0, 1), y = c(0, 1)), "continuous") plot(simple_p, main = "Case study of n_extra_grid argument") lines(simple_p, n_extra_grid = 0, col = "red") # R-functions are plotted with histogram plot(as_r(d_norm_1))
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