sample size.
If
length(n) is larger than 1, then
length(n) random values are returned.
OPTIONAL ARGUMENTS:
distribution
character string that specifies the distribution.
Possible values are:
normal,
beta,
cauchy,
chisquare,
exponential,
f,
gamma,
lognormal,
logistic,
t,
uniform,
weibull,
binomial,
geometric,
hypergeometric,
negbinomial,
poisson.
seed
be an integer between 0 and 1000.
Sets the value of the
.Random.seed object in the working directory.
Different seeds make different sequence of random numbers.
print.object.p
if
TRUE, the result of the test is printed.
df1
parameter of a distribution, when
distribution is
"chisquare",
"f", or
"t".
df2
parameter of a distribution, when
distribution is
"f".
max
parameter of a distribution, when
distribution is
"uniform".
min
parameter of a distribution, when
distribution is
"uniform".
mean
parameter of a distribution, when
distribution is
"exponential",
"lognormal",
"normal",
"poisson".
sd
parameter of a distribution, when
distribution is
"normal",
"lognormal".
location
parameter of a distribution, when
distribution is
"cauchy",
"logistic".
scale
parameter of a distribution, when
distribution is
"cauchy",
"logistic",
"weibull".
shape1
parameter of a distribution, when
distribution is
"beta",
"gamma",
"weibull".
shape2
parameter of a distribution, when
distribution is
"beta".
prob
parameter of a distribution, when
distribution is
"binomial",
"geometric",
"negbinomial".
size
parameter of a distribution, when
distribution is
"binomial",
"negbinomial".
k
parameter of a distribution, when
distribution is
"negbinomial".
m
parameter of a distribution, when
distribution is
"hypergeometric".
n
parameter of a distribution, when
distribution is
"hypergeometric".
VALUE:
invisibly returns a data frame containing the random numbers generated
from the chosen distribution with the specified parameters.
SIDE EFFECTS:
If
print.object.p is
TRUE the random numbers are printed.