概率分佈函式的四種形式（R）
（1）The Normal Distribution
Usage：
dnorm(x, mean = 0, sd = 1, log = FALSE)
pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
qnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
rnorm(n, mean = 0, sd = 1)
Arguments：
|
x,q |
vector of quantiles. |
|
p |
vector of probabilities. |
|
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
|
mean |
vector of means. |
|
sd |
vector of standard deviations. |
|
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
|
lower.tail |
logical; if TRUE (default), probabilities are P[X ≤ x] otherwise, P[X > x] |
（2）卡方分佈
Usage：
dchisq(x, df, ncp=0, log = FALSE)
pchisq(q, df, ncp=0, lower.tail = TRUE, log.p = FALSE)
qchisq(p, df, ncp=0, lower.tail = TRUE, log.p = FALSE)
rchisq(n, df, ncp=0)
Arguments：
|
x, q |
vector of quantiles. |
|
p |
vector of probabilities. |
|
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
|
df |
degrees of freedom (non-negative, but can be non-integer). |
|
ncp |
non-centrality parameter (non-negative). |
|
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
|
lower.tail |
logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x]. |
（3）F分佈
Usage：
df(x, df1, df2, ncp, log = FALSE)
pf(q, df1, df2, ncp, lower.tail = TRUE, log.p = FALSE)
qf(p, df1, df2, ncp, lower.tail = TRUE, log.p = FALSE)
rf(n, df1, df2, ncp)
Arguments：
|
x, q |
vector of quantiles. |
|
p |
vector of probabilities. |
|
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
|
df1, df2 |
degrees of freedom. Inf is allowed. |
|
ncp |
non-centrality parameter. If omitted the central F is assumed. |
|
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
|
lower.tail |
logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x]. |
（4）T分佈
Usage：
dt(x, df, ncp, log = FALSE)
pt(q, df, ncp, lower.tail = TRUE, log.p = FALSE)
qt(p, df, ncp, lower.tail = TRUE, log.p = FALSE)
rt(n, df, ncp)
Arguments：
|
x, q |
vector of quantiles. |
|
p |
vector of probabilities. |
|
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
|
df |
degrees of freedom (> 0, maybe non-integer). df = Inf is allowed. |
|
ncp |
non-centrality parameter delta; currently except for rt(), only for abs(ncp) <= 37.62. If omitted, use the central t distribution. |
|
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
|
lower.tail |
logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x]. |