df(x, df1, df2, log=F) pf(q, df1, df2, ncp=0) qf(p, df1, df2) rf(n, df1, df2, bigdata=F)
bdVector
of (positive) quantiles.
Missing values (
NA
s) are allowed.
bdVector
of (positive) quantiles.
Missing values (
NA
s) are allowed.
bdVector
of probabilities.
Missing values (
NA
s) are allowed.
length(n)
is larger than 1, then
length(n)
random values are returned.
p
or
q
or the number of
deviates generated.
Non-integer values are allowed, but missing values are not.
p
or
q
or the number of
deviates generated.
Non-integer values are allowed, but missing values are not.
bdVector
of positive numbers giving the noncentrality parameter.
See
Chisquare
for a description of the parameterization.
TRUE
, an object of type
bdVector
is returned.
Otherwise, a
vector
object is returned. This argument can be used only if the bigdata library section has been loaded.
TRUE
,
df
will return
the log of the density, not the density itself.
df
),
probability (
pf
),
quantile (
qf
), or
random sample (
rf
)
for the F-distribution with degrees of freedom
df1
and
df2
.
rf
causes creation of the dataset
.Random.seed
if it does
not already exist, otherwise its value is updated.
Missing values (NA) are allowed.
Elements of
q
or
p
that are missing will cause the corresponding elements of the result to be missing.
The F distribution takes values on the positive real line. It is the
distribution of the ratio of two chi-squared variates each divided by
its degrees of freedom.
The chi-square in the numerator has
df1
degrees of freedom, and the
chi-square in the denominator has
df2
degrees of freedom.
By far the most common use of the F distribution is for testing
hypotheses under the Gaussian assumption (see
Normal
).
The F can also be used to give an approximate confidence interval for
the binomial distribution.
For details on the uniform random number generator implemented in S-PLUS,
see the
set.seed
help file.
Johnson, N. L. and Kotz, S. (1970). Continuous Univariate Distributions, vol. 2. Houghton-Mifflin, Boston.
1 - pf(stat, 4, 12) # p-value of stat rf(10, 5, 15) #sample of 10 with 5 and 15 degrees of freedom # power of a test for several noncentrality values 1 - pf(qf(.95, 4, 5), 4, 5, 0:10)