ggdist: student_t – R documentation

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student_t

Scaled and shifted Student's t distribution

Description

Density, distribution function, quantile function and random generation for the scaled and shifted Student's t distribution, parameterized by degrees of freedom (df), location (mu), and scale (sigma).

Usage

dstudent_t(x, df, mu = 0, sigma = 1, log = FALSE)

pstudent_t(q, df, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)

qstudent_t(p, df, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE)

rstudent_t(n, df, mu = 0, sigma = 1)

Arguments

`x`	vector of quantiles.
`df`	degrees of freedom (> 0, maybe non-integer). `df = Inf` is allowed.
`mu`	Location parameter (median)
`sigma`	Scale parameter
`log`	logical; if TRUE, probabilities p are given as log(p).
`q`	vector of quantiles.
`lower.tail`	logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x].
`log.p`	logical; if TRUE, probabilities p are given as log(p).
`p`	vector of probabilities.
`n`	number of observations. If `length(n) > 1`, the length is taken to be the number required.

Value

dstudent_t gives the density
pstudent_t gives the cumulative distribution function (CDF)
qstudent_t gives the quantile function (inverse CDF)
rstudent_t generates random draws.

The length of the result is determined by n for rstudent_t, and is the maximum of the lengths of the numerical arguments for the other functions.

The numerical arguments other than n are recycled to the length of the result. Only the first elements of the logical arguments are used.

Examples

library(dplyr)
library(ggplot2)
library(forcats)

expand.grid(
  df = c(3,5,10,30),
  scale = c(1,1.5)
) %>%
  ggplot(aes(y = 0, dist = "student_t", arg1 = df, arg2 = 0, arg3 = scale, color = ordered(df))) +
  stat_dist_slab(p_limits = c(.01, .99), fill = NA) +
  scale_y_continuous(breaks = NULL) +
  facet_grid( ~ scale) +
  labs(
    title = "dstudent_t(x, df, 0, sigma)",
    subtitle = "Scale (sigma)",
    y = NULL,
    x = NULL
  ) +
  theme_ggdist() +
  theme(axis.title = element_text(hjust = 0))

ggdist

Visualizations of Distributions and Uncertainty

v2.4.0

GPL (>= 3)

Authors

Matthew Kay [aut, cre]

Initial release

2021-01-03