Noncentral *F* random numbers

`R = ncfrnd(NU1,NU2,DELTA)`

R = ncfrnd(NU1,NU2,DELTA,m,n,...)

R
= ncfrnd(NU1,NU2,DELTA,[m,n,...])

`R = ncfrnd(NU1,NU2,DELTA)`

returns a matrix
of random numbers chosen from the noncentral *F* distribution
with corresponding numerator degrees of freedom in `NU1`

,
denominator degrees of freedom in `NU2`

, and positive
noncentrality parameters in `DELTA`

. `NU1`

, `NU2`

,
and `DELTA`

can be vectors, matrices, or multidimensional
arrays that have the same size, which is also the size of `R`

.
A scalar input for `NU1`

, `NU2`

,
or `DELTA`

is expanded to a constant matrix with
the same dimensions as the other inputs.

`R = ncfrnd(NU1,NU2,DELTA,m,n,...)`

or ```
R
= ncfrnd(NU1,NU2,DELTA,[m,n,...])
```

generates an `m`

-by-`n`

-by-...
array. The `NU1`

, `NU2`

, `DELTA`

parameters
can each be scalars or arrays of the same size as `R`

.

Compute six random numbers from a noncentral *F* distribution
with 10 numerator degrees of freedom, 100 denominator degrees of freedom
and a noncentrality parameter, δ, of 4.0. Compare this to the *F* distribution
with the same degrees of freedom.

r = ncfrnd(10,100,4,1,6) r = 2.5995 0.8824 0.8220 1.4485 1.4415 1.4864 r1 = frnd(10,100,1,6) r1 = 0.9826 0.5911 1.0967 0.9681 2.0096 0.6598

[1] Johnson, N., and S. Kotz. *Distributions
in Statistics: Continuous Univariate Distributions-2.* Hoboken,
NJ: John Wiley & Sons, Inc., 1970, pp. 189–200.

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