dcauchy(x, location=0, scale=1, log=F) pcauchy(q, location=0, scale=1) qcauchy(p, location=0, scale=1) rcauchy(n, location=0, scale=1, bigdata=F)
bdVector of quantiles.
Missing values (
NAs) are allowed.
bdVector of quantiles.
Missing values (
NAs) are allowed.
bdVector of probabilities.
Missing values (
NAs) are allowed.
length(n) is larger than 1, then
length(n) random values are returned.
bdVector of location parameters.
This is replicated to be the same length as
p or
q or the number of
deviates generated.
Missing values are not accepted.
bdVector of (positive) scale parameters.
This is replicated to be the same length as
p or
q or the number of
deviates generated.
Missing values are not accepted.
TRUE, an object of type
bdVector is returned.
Otherwise, a
vector object is returned. This argument can be used only if the bigdata library section has been loaded.
TRUE,
dcauchy will return
the log of the density, not the density itself.
dcauchy),
probability (
pcauchy),
quantile (
qcauchy), or
random sample (
rcauchy)
for the cauchy distribution with parameters
location and
scale.
rcauchy causes creation of the dataset
.Random.seed if it does
not already exist, otherwise its value is updated.
Elements of
q or
p that are missing will cause the corresponding elements of the result to be missing.
The Cauchy is a real valued distribution symmetric about
location, and
has long enough tails that the expectation does not exist.
The default distribution is the same as Student's t distribution with
one degree of freedom (see
T).
The harmonic mean of variates that have positive density at 0 is typically
distributed as Cauchy. The Cauchy also appears in the theory of Brownian
motion.
For details on the uniform random number generator implemented in S-PLUS,
see the
set.seed help file.
Johnson, N. L. and Kotz, S. (1970). Continuous Univariate Distributions, vol. 1. Houghton-Mifflin, Boston.
rcauchy(20,0,10) #sample of 20, location 0, scale 10