dgamma(x, shape, rate = 1, scale = 1/rate, log = FALSE) # density pgamma(q, shape, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE) # probability qgamma(p, shape, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE) # quantile rgamma(n, shape, rate = 1, scale = 1/rate) # random
x, q | numeric vectors in the range [0, Inf) that specify the quantiles. |
p | a numeric vector in the range [0, 1] that specifies the probabilities. |
n | an integer scalar in the range [0, Inf) that specifies the number of random samples requested. If the input value is not an integer, it is truncated. If length(n) is greater than 1, the random function returns length(n) random samples. |
shape | a numeric vector in the range [0, Inf) that specifies the shape parameter. |
rate | a numeric vector in the range [0, Inf) that specifies the inverse of the scale parameter. |
scale | a numeric vector in the range [0, Inf) that specifies the scale parameter. Ignored if rate is supplied. |
log | a logical value. If FALSE (default), the density function returns the density itself. If TRUE, it returns the log of the density. |
lower.tail | a logical value. If TRUE (default), the probability supplied to the quantile function or returned by the probability function is P[X <= x]. If FALSE, it is P[X > x]. |
log.p | a logical value. If FALSE (default), the probability supplied to the quantile function or returned by the probability function is the probability itself. If TRUE, it is the log of the probability. |
# sample of 20 with shape parameter 10 rgamma(20, 10)# the probability that a value from the gamma # distribution with shape 1.5 is less than 1.2 pgamma(1.2, 1.5)
# compute a vector of quantiles (x <- qgamma(seq(.001, .999, len = 10), 1.5))
# density for shape 1.5 dgamma(x, 1.5)