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cdffnc(1)                      Scilab Function                      cdffnc(1)
NAME
  cdffnc - cumulative distribution function non-central f-distribution

CALLING SEQUENCE
  [P,Q]=cdffnc("PQ",F,Dfn,Dfd,Pnonc)
  [F]=cdffnc("F",Dfn,Dfd,Pnonc,P,Q);
  [Dfn]=cdffnc("Dfn",Dfd,Pnonc,P,Q,F);
  [Dfd]=cdffnc("Dfd",Pnonc,P,Q,F,Dfn)
  [Pnonc]=cdffnc("Pnonc",P,Q,F,Dfn,Dfd);

PARAMETERS

  P,Q,F,Dfn,Dfd,Pnonc
            : six real vectors of the same size.

  P,Q (Q=1-P)
              The integral from 0 to F of the non-central f-density.  Input
            range: [0,1-1E-16).

  F         : Upper limit of integration of the non-central f-density.  Input
            range: [0, +infinity).  Search range: [0,1E300]

  Dfn       : Degrees of freedom of the numerator sum of squares.  Input
            range: (0, +infinity).  Search range: [ 1E-300, 1E300]

  Dfd       : Degrees of freedom of the denominator sum of squares.  Must be
            in range: (0, +infinity).  Input range: (0, +infinity).  Search
            range: [ 1E-300, 1E300]

  Pnonc     : The non-centrality parameter Input range: [0,infinity) Search
            range: [0,1E4]

DESCRIPTION
  Calculates any one parameter of the Non-central F distribution given values
  for the others.

  Formula  26.6.20   of   Abramowitz   and   Stegun,  Handbook  of Mathemati-
  cal  Functions (1966) is used to compute the cumulative distribution func-
  tion.

  Computation of other parameters involve a seach for a value that produces
  the desired  value  of P.   The search relies  on  the monotinicity of P
  with the other parameter.

  The computation time  required for this  routine is proportional to the
  noncentrality  parameter  (PNONC).  Very large  values of this parameter
  can consume immense  computer resources.  This is why the search range is
  bounded by 10,000.
  The  value  of the  cumulative  noncentral F distribution is not neces-
  sarily monotone in either degrees  of freedom.  There  thus may be two
  values that provide a given  CDF value.  This routine assumes monotonicity
  and will find  an arbitrary one of the two values.
  From DCDFLIB: Library of Fortran Routines for Cumulative Distribution Func-
  tions, Inverses, and Other Parameters (February, 1994) Barry W. Brown,
  James Lovato and Kathy Russell. The University of Texas.