Bernoulli

dbern

pbern

qbern

rbern

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