Functions to check performance of distribution and quantile
functions. Applying the distribution function followed by the quantile
function to a set of numbers should reproduce the original set of
numbers. Likewise applying the quantile function followed by the
distribution function to numbers in the range (0,1) should produce the
original numbers.
Character. The root name of the distribution to be tested.
qs
Numeric. Set of quantiles to which quantile function then
distribution function will be applied. See Details.
n
Numeric. Number of values to be sampled from the
distribution. See Details.
x
Numeric. Values at which the distribution function is to be
evaluated. If NULL values are drawn at random from the
distribution.
intTol
Value of rel.tol and hence abs.tol in calls
to integrate. See integrate.
uniTol
Value of tol in calls to uniroot. See
uniroot.
method
Character. If "spline" quantiles are found from a
spline approximation to the distribution function. If
"integrate", the distribution function used is always obtained
by integration.
...
Additional arguments to allow specification of the
parameters of the distribution.
Details
inversionTestpq takes a sample from the specified distribution
of size n then applies the distribution function, followed by
the quantile function.
inversionTestqp applies the quantile function, followed by
the distribution function to the set of quantiles specified by
qs.
In both cases the starting and ending values should be the same.
These tests are used in base R to check the standard distribution
functions. The code may be found in the file d-p-q-r.tests.R in
the tests directory.
Value
inversionTestpq returns a list with components:
qpx
Numeric. The result of applying the distribution function
(‘p’ function) then the quantile function (‘q’ function) to
the randomly generated set of x values.
x
Numeric. The set of x values generated by the ‘r’
function.
diffs
Numeric. The differences qpx minus x.
n
Numeric. Number of values sampled from the distribution.
inversionTestqp returns a list with components:
pqqs
Numeric. The result of applying the quantile function
(‘q’ function) then the distribution function (‘p’ function) to
the quantiles qs.