size
successes occur in a sequence of Bernoulli trials.
dnbinom(x, size, prob, log=F) pnbinom(q, size, prob) qnbinom(p, size, prob) rnbinom(n, size, prob, bigdata=F)
bdVector of (positive) quantiles.
Missing values (
NAs) are allowed.
bdVector of (positive) quantiles.
Missing values (
NAs) are allowed.
bdVector of probabilities.
Missing values (
NAs) are allowed.
bdVector of positive integers; the Negative Binomial represents the
number of failures (or tails in coin tossing) before
size successes
(or heads in coin tossing) are achieved where the
probability of a success (or of a head) is
prob.
bdVector of probabilities of a success.
If
length(n) is larger than 1, then
length(n) random values are returned.
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,
dnbinom will return
the log of the density, not the density itself.
dnbinom),
probability (
pnbinom),
quantile (
qnbinom), or
random sample (
rnbinom)
for the Negative Binomial distribution with parameters
size and
prob.
The quantile is defined as the smallest value
q such that Pr(Negative
Binomial random variate <=
x) >=
p.
rbinom causes the creation of the dataset
.Random.seed if
it does not already exist, otherwise its value is updated.
q or
p that are missing will cause the
corresponding elements of the result to be missing.
For details on the uniform random number generator implemented in S-PLUS,
see the
set.seed help file.
rbinom(20,10,0.5) # sample of size 20 with mean 10*0.5 = 5