Illustrated probability calculations from distributions
Illustrated probability calculations from distributions
pdist(
dist = "norm",
q,
plot = TRUE,
verbose = FALSE,
invisible = FALSE,
digits = 3L,
xlim,
ylim,
resolution = 500L,
return = c("values", "plot"),
...,
refinements = list()
)
xpgamma(
q,
shape,
rate = 1,
scale = 1/rate,
lower.tail = TRUE,
log.p = FALSE,
...
)
xpt(q, df, ncp, lower.tail = TRUE, log.p = FALSE, ...)
xpchisq(q, df, ncp = 0, lower.tail = TRUE, log.p = FALSE, ...)
xpf(q, df1, df2, lower.tail = TRUE, log.p = FALSE, ...)
xpbinom(q, size, prob, lower.tail = TRUE, log.p = FALSE, ...)
xppois(q, lambda, lower.tail = TRUE, log.p = FALSE, ...)
xpgeom(q, prob, lower.tail = TRUE, log.p = FALSE, ...)
xpnbinom(q, size, prob, mu, lower.tail = TRUE, log.p = FALSE, ...)
xpbeta(q, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE, ...)dist |
a character description of a distribution, for example
|
q |
a vector of quantiles |
plot |
a logical indicating whether a plot should be created |
verbose |
a logical |
invisible |
a logical |
digits |
the number of digits desired |
xlim |
x limits |
ylim |
y limits |
resolution |
Number of points used for detecting discreteness and generating plots. The default value of 5000 should work well except for discrete distributions that have many distinct values, especially if these values are not evenly spaced. |
return |
If |
... |
Additional arguments, typically for fine tuning the plot. |
refinements |
A list of refinements to the plot. See |
shape |
shape and scale parameters. Must be positive,
|
rate |
an alternative way to specify the scale. |
scale |
shape and scale parameters. Must be positive,
|
lower.tail |
logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x]. |
log.p |
logical; if |
df |
degrees of freedom (> 0, maybe non-integer). |
ncp |
non-centrality parameter delta;
currently except for |
df1 |
degrees of freedom. |
df2 |
degrees of freedom. |
size |
number of trials (zero or more). |
prob |
probability of success on each trial. |
lambda |
vector of (non-negative) means. |
mu |
alternative parametrization via mean: see ‘Details’. |
shape1 |
non-negative parameters of the Beta distribution. |
shape2 |
non-negative parameters of the Beta distribution. |
The most general function is pdist which can work with
any distribution for which a p-function exists. As a convenience, wrappers are
provided for several common distributions.
A vector of probabilities; a plot is printed as a side effect.
pdist("norm", -2:2)
pdist("norm", seq(80,120, by = 10), mean = 100, sd = 10)
pdist("chisq", 2:4, df = 3)
pdist("f", 1, df1 = 2, df2 = 10)
pdist("gamma", 2, shape = 3, rate = 4)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.