Description Usage Arguments Details Examples
Density, distribution function, quantile function and random generation for the binomial intersection distribution.
1 2 3 4 5 6 7 |
n |
An integer specifying the number of categories in the urns. |
A |
A vector of integers specifying the numbers of balls drawn from each urn. The length of the vector equals the number of urns. |
range |
A vector of integers specifying the intersection sizes for which probabilities (dhint) or cumulative probabilites (phint) should be computed (can be a single number). If range is NULL (default) then probabilities will be returned over the entire range of possible values. |
log |
Logical. If TRUE, probabilities p are given as log(p). Defaults to FALSE. |
vals |
A vector of integers specifying the intersection sizes for which probabilities (dhint) or cumulative probabilites (phint) should be computed (can be a single number). If range is NULL (default) then probabilities will be returned over the entire range of possible values. |
upper.tail |
Logical. If TRUE, probabilities are P(X >= v), else P(X <= v). Defaults to TRUE. |
log.p |
Logical. If TRUE, probabilities p are given as log(p). Defaults to FALSE. |
p |
A probability between 0 and 1. |
num |
An integer specifying the number of random numbers to generate. Defaults to 5. |
The binomial intersection distribution is given by
P(X = v|N) = choose(b,v)*((prod_{i=1}^{N-1} p_i)^v) * (1 - prod_{i=1}^{N-1} p_i)^(b-v)
where b gives the sample size which is smallest. This is an approximation for the hypergeometric intersection distribution when n is large and b is small relative to the samples taken from the N-1 other urns.
1 2 3 4 5 6 7 8 9 10 11 | ## Generate the distribution of intersections sizes:
dd <- dbint(20, c(10, 12, 11, 14))
## Restrict the range of intersections.
dd <- dbint(20, c(10, 12), range = 0:5)
## Generate cumulative probabilities.
pp <- pbint(29, c(15, 8), vals = 5)
pp <- pbint(29, c(15, 8), vals = 2, upper.tail = FALSE)
## Extract quantiles:
qq <- qbint(0.15, 23, c(12, 10))
## Generate random samples from Binomial intersection distributions.
rr <- rbint(num = 10, 18, c(9, 14))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.