R软件中的泊松分布
(2011-10-12 17:07:09)
标签:
杂谈 |
分类: R软件学习 |
The Poisson Distribution
Description
Density, distribution function, quantile function and random
generation for the Poisson distribution with
parameter lambda
.
Usage
dpois(x, lambda, log = FALSE) ppois(q, lambda, lower.tail = TRUE, log.p = FALSE) qpois(p, lambda, lower.tail = TRUE, log.p = FALSE) rpois(n, lambda)
Arguments
x |
vector of (non-negative integer) quantiles. |
q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of random values to return. |
lambda |
vector of (non-negative) means. |
log,
log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if
TRUE (default), probabilities are |
Details
The Poisson distribution has density
p(x) = λ^x exp(-λ)/x!
for
If an element
of x
dpois
dbinom
.
The quantile is right
continuous: qpois(p,
lambda)
Setting lower.tail =
FALSE
lower.tail =
TRUE
Value
dpois
ppois
qpois
rpois
Invalid lambda
NaN
, with a
warning.
Source
dpois
dbinom
).
ppois
pgamma
.
qpois
rpois
Ahrens, J. H. and Dieter, U. (1982). Computer generation of
Poisson deviates from modified normal
distributions.
See Also
Distributions dbinom
dnbinom
Examples
require(graphics) -log(dpois(0:7, lambda=1) * gamma(1+ 0:7)) # == 1 Ni <- rpois(50, lambda = 4); table(factor(Ni, 0:max(Ni))) 1 - ppois(10*(15:25), lambda=100) # becomes 0 (cancellation) ppois(10*(15:25), lambda=100, lower.tail=FALSE) # no cancellation par(mfrow = c(2, 1)) x <- seq(-0.01, 5, 0.01) plot(x, ppois(x, 1), type="s", ylab="F(x)", main="Poisson(1) CDF") plot(x, pbinom(x, 100, 0.01),type="s", ylab="F(x)", main="Binomial(100, 0.01) CDF")