Geometric
The Geometric Distribution

### Description

Calculates density, cumulative probability, quantile, and generate random sample for the geometric distribution (discrete).

### Usage

    dgeom(x, prob, log = FALSE) # density
    pgeom(q, prob, lower.tail = TRUE, log.p = FALSE) # probability
    qgeom(p, prob, lower.tail = TRUE, log.p = FALSE) # quantile
    rgeom(n, prob) # random

### Arguments

x, q | numeric vectors in the range [0, Inf) that specify the quantiles.
p | a numeric vector in the range [0, 1] that specifies the probabilities.
n | an integer value in the range [0, Inf) that specifies the number of random samples requested. If the input value is not an integer, it is truncated. If length(n) is greater than 1, the random function returns length(n) random samples.
prob | a numeric vector in the range [0, 1] that specifies the probability of a success in a Bernoulli trial.
log | a logical value. If FALSE (default), the density function returns the density itself. If TRUE, it returns the log of the density.
lower.tail | a logical value. If TRUE (default), the probability supplied to the quantile function or returned by the probability function is P[X <= x]. If FALSE, it is P[X > x].
log.p | a logical value. If FALSE (default), the probability supplied to the quantile function or returned by the probability function is the probability itself. If TRUE, it is the log of the probability.

### Details

The distribution parameter(s) are replicated cyclically to be the same length as the input x, q, p, or the number of random samples requested.
Missing values (NAs) in the input or the distribution parameter(s) will cause the corresponding elements of the result to be missing.
Value
returns density (dgeom), cumulative probability (pgeom), quantile (qgeom), or random sample (rgeom) for the geometric distribution with parameter prob. The quantile is defined as the smallest value q such that Pr(geometric random variate <= x) >= p.
Side Effects
If the .Random.seed dataset exists, the random sample function updates its value. The random sample function creates the .Random.seed dataset if it does not exist.
Background
The geometric distribution is the discrete probability distribution of the number of failures before the first success in a sequence of independent experiments, each of which has two possible outcomes (yes/no) (i.e., a Bernoulli trial) and yields success with probability prob. It has support on the integer set {0, 1, 2, 3, …}.
See Also
set.seed, NegBinomial, Binomial
Examples

    rgeom(20, 0.6)  #sample of size 20 with parameter 0.6

Package stats version 6.1.5-18
Package Index