Functions to compute the probability density function, cumulative distribution function, and quantile function for the Bernoulli distribution.
Usage
bernoulli_distribution(p_success)
bernoulli_pdf(x, p_success)
bernoulli_lpdf(x, p_success)
bernoulli_cdf(x, p_success)
bernoulli_lcdf(x, p_success)
bernoulli_quantile(p, p_success)Value
A single numeric value with the computed probability density, log-probability density, cumulative distribution, log-cumulative distribution, or quantile depending on the function called.
See also
Boost Documentation for more details on the mathematical background.
Examples
# Bernoulli distribution with p_success = 0.5
dist <- bernoulli_distribution(0.5)
# Apply generic functions
cdf(dist, 0.5)
#> [1] 0.8183099
logcdf(dist, 0.5)
#> [1] -0.2005142
pdf(dist, 0.5)
#> [1] 0.6366198
logpdf(dist, 0.5)
#> [1] -0.4515827
hazard(dist, 0.5)
#> [1] 3.503877
chf(dist, 0.5)
#> [1] 1.705453
mean(dist)
#> [1] 0.5
median(dist)
#> [1] 0
mode(dist)
#> [1] 1
range(dist)
#> [1] 0 1
quantile(dist, 0.2)
#> [1] 0
standard_deviation(dist)
#> [1] 0.5
support(dist)
#> [1] 0 1
variance(dist)
#> [1] 0.25
skewness(dist)
#> [1] 0
kurtosis(dist)
#> [1] 1
kurtosis_excess(dist)
#> [1] -2
# Convenience functions
bernoulli_pdf(1, 0.5)
#> [1] 0.5
bernoulli_lpdf(1, 0.5)
#> [1] -0.6931472
bernoulli_cdf(1, 0.5)
#> [1] 1
bernoulli_lcdf(1, 0.5)
#> [1] 0
bernoulli_quantile(0.5, 0.5)
#> [1] 0