Bernoulli

dbern

pbern

qbern

rbern

x, q

probability of success; (<code>0 &lt; prob &lt; 1</code>).

prob

logical; if TRUE, probabilities p are given as log(p).

log, log.p

logical; if TRUE (default), probabilities are \(P[X \le x]\)
otherwise, \(P[X &gt; x]\).

lower.tail

number of observations. If <code>length(n) &gt; 1</code>,
the length is taken to be the number required.

Probability mass function, distribution function, quantile function and random generation
for the Bernoulli distribution.

distribution

Density, distribution function, quantile function
and random generation for a number of univariate
and multivariate distributions. This package implements the
following distributions: Bernoulli, beta-binomial, beta-negative
binomial, beta prime, Bhattacharjee, Birnbaum-Saunders,
bivariate normal, bivariate Poisson, categorical, Dirichlet,
Dirichlet-multinomial, discrete gamma, discrete Laplace,
discrete normal, discrete uniform, discrete Weibull, Frechet,
gamma-Poisson, generalized extreme value, Gompertz,
generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t,
Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy,
Laplace, location-scale t, logarithmic, Lomax, multivariate
hypergeometric, multinomial, negative hypergeometric,
non-standard beta, normal mixture, Poisson mixture, Pareto,
power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam,
slash, triangular, truncated binomial, truncated normal,
truncated Poisson, Tukey lambda, Wald, zero-inflated binomial,
zero-inflated negative binomial, zero-inflated Poisson.

Tymoteusz Wolodzko

extraDistr

Additional Univariate and Multivariate Distributions

Bernoulli function

<dl><dt>x, q</dt>
<dd>vector of quantiles.</dd>
<dt>prob</dt>
<dd>probability of success; (<code>0 &lt; prob &lt; 1</code>).</dd>
<dt>log, log.p</dt>
<dd>logical; if TRUE, probabilities p are given as log(p).</dd>
<dt>lower.tail</dt>
<dd>logical; if TRUE (default), probabilities are \(P[X \le x]\)
otherwise, \(P[X &gt; x]\).</dd>
<dt>p</dt>
<dd>vector of probabilities.</dd>
<dt>n</dt>
<dd>number of observations. If <code>length(n) &gt; 1</code>,
the length is taken to be the number required.</dd></dl>

Arguments

Bernoulli distribution — Bernoulli

<dl>

<dt>x, q</dt>
<dd>vector of quantiles.</dd>


<dt>prob</dt>
<dd>probability of success; (<code>0 &lt; prob &lt; 1</code>).</dd>


<dt>log, log.p</dt>
<dd>logical; if TRUE, probabilities p are given as log(p).</dd>


<dt>lower.tail</dt>
<dd>logical; if TRUE (default), probabilities are \(P[X \le x]\)
otherwise, \(P[X &gt; x]\).</dd>


<dt>p</dt>
<dd>vector of probabilities.</dd>


<dt>n</dt>
<dd>number of observations. If <code>length(n) &gt; 1</code>,
the length is taken to be the number required.</dd>

</dl>

Bernoulli: Bernoulli distribution

Description

Usage

Arguments

See Also

Examples