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21.1 Beta distribution

21.1.1 Probability density function

If αR+ and βR+, then for θ(0,1), Beta(θ|α,β)=1B(α,β)θα1(1θ)β1, where the beta function B() is as defined in section combinatorial functions.

Warning: If θ=0 or θ=1, then the probability is 0 and the log probability is . Similarly, the distribution requires strictly positive parameters, α,β>0.

21.1.2 Sampling statement

theta ~ beta(alpha, beta)

Increment target log probability density with beta_lupdf(theta | alpha, beta).
Available since 2.0

21.1.3 Stan functions

real beta_lpdf(reals theta | reals alpha, reals beta)
The log of the beta density of theta in [0,1] given positive prior successes (plus one) alpha and prior failures (plus one) beta
Available since 2.12

real beta_lupdf(reals theta | reals alpha, reals beta)
The log of the beta density of theta in [0,1] given positive prior successes (plus one) alpha and prior failures (plus one) beta dropping constant additive terms
Available since 2.25

real beta_cdf(reals theta, reals alpha, reals beta)
The beta cumulative distribution function of theta in [0,1] given positive prior successes (plus one) alpha and prior failures (plus one) beta
Available since 2.0

real beta_lcdf(reals theta | reals alpha, reals beta)
The log of the beta cumulative distribution function of theta in [0,1] given positive prior successes (plus one) alpha and prior failures (plus one) beta
Available since 2.12

real beta_lccdf(reals theta | reals alpha, reals beta)
The log of the beta complementary cumulative distribution function of theta in [0,1] given positive prior successes (plus one) alpha and prior failures (plus one) beta
Available since 2.12

R beta_rng(reals alpha, reals beta)
Generate a beta variate with positive prior successes (plus one) alpha and prior failures (plus one) beta; may only be used in transformed data and generated quantities blocks. For a description of argument and return types, see section vectorized PRNG functions.
Available since 2.18