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 (
NAs) are allowed.
bdVector of (positive) quantiles.
Missing values (
NAs) are allowed.
bdVector of probabilities.
Missing values (
NAs) 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)