BetaBinomial {TailRank} | R Documentation |

## The Beta-Binomial Distribution

### Description

Density, distribution function, quantile function, and random generation
for the beta-binomial distribution. A variable with a beta-binomial
distribution is distributed as binomial distribution with parameters
`N`

and `p`

, where the probability `p`

of success iteself
has a beta distribution with parameters `u`

and `v`

.

### Usage

dbb(x, N, u, v)
pbb(q, N, u, v)
qbb(p, N, u, v)
rbb(n, N, u, v)

### Arguments

`x` |
vector of qauntiles |

`q` |
vector of quantiles |

`p` |
vector of probabilities |

`n` |
number of observations |

`N` |
number of trials ( a positive integer) |

`u` |
first positive parameter of the beta distribution |

`v` |
second positive parameter of the beta distribution |

### Details

The beta-binomial distribution with parameters *N*, *u*, and
*v* has density given by

*
choose(N, x) * Beta(x + u, N - x + v) / Beta(u,v)
*

for *u > 0*, *v > 0*, a positive integer *N*, and any
nonnegative integer *x*. Although one can express the integral
in closed form using generalized hypergeometric functions, the
implementation of distribution function used here simply relies on the
the cumulative sum of the density.

The mean and variance of the beta-binomial distribution can be
computed explicitly as

*
mu = frac{nu}/{u+v}
*

and

*
sigma^2 = frac{nuv(n+u+v)}{(u+v)^2 (1+u+v)}
*

### Value

`dbb`

gives the density, `pbb`

gives the distribution function,
`qbb`

gives the quantile function, and `rbb`

generates random
deviates.

### Author(s)

Kevin R. Coombes <kcoombes@mdanderson.org>

### See Also

`dbeta`

for the beta distribution and
`dbinom`

for the binomial distribution.

### Examples

# set up parameters
w <- 10
u <- 0.3*w
v <- 0.7*w
N <- 12
# generate random values from the beta-binomial
x <- rbb(1000, N, u, v)
# check that the empirical summary matches the theoretical one
summary(x)
qbb(c(0.25, 0.50, 0.75), N, u, v)
# check that the empirpical histogram matches te theoretical density
hist(x, breaks=seq(-0.5, N + 0.55), prob=TRUE)
lines(0:N, dbb(0:N, N, u,v), type='b')

[Package

*TailRank* version 2.5.0

Index]