g01fm returns the deviate associated with the lower tail probability of the distribution of the Studentized range statistic.
Syntax
C# |
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public static double g01fm( double p, double v, int ir, out int ifail ) |
Visual Basic |
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Public Shared Function g01fm ( _ p As Double, _ v As Double, _ ir As Integer, _ <OutAttribute> ByRef ifail As Integer _ ) As Double |
Visual C++ |
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public: static double g01fm( double p, double v, int ir, [OutAttribute] int% ifail ) |
F# |
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static member g01fm : p : float * v : float * ir : int * ifail : int byref -> float |
Parameters
- p
- Type: System..::..DoubleOn entry: the lower tail probability for the Studentized range statistic, .Constraint: .
- v
- Type: System..::..DoubleOn entry: , the number of degrees of freedom.Constraint: .
- ir
- Type: System..::..Int32On entry: , the number of groups.Constraint: .
- ifail
- Type: System..::..Int32%On exit: unless the method detects an error or a warning has been flagged (see [Error Indicators and Warnings]).
Return Value
g01fm returns the deviate associated with the lower tail probability of the distribution of the Studentized range statistic.
Description
The externally Studentized range, , for a sample, , is defined as
where is an independent estimate of the standard error of the . The most common use of this statistic is in the testing of means from a balanced design. In this case for a set of group means, , the Studentized range statistic is defined to be the difference between the largest and smallest means, and , divided by the square root of the mean-square experimental error, , over the number of observations in each group, , i.e.,
The Studentized range statistic can be used as part of a multiple comparisons procedure such as the Newman–Keuls procedure or Duncan's multiple range test (see Montgomery (1984) and Winer (1970)).
For a Studentized range statistic the probability integral, , for degrees of freedom and groups, can be written as:
where
For a given probability , the deviate is found as the solution to the equation
using
c05az
.
Initial estimates are found using the approximation given in Lund and Lund (1983) and a simple search procedure.
(1) |
References
Lund R E and Lund J R (1983) Algorithm AS 190: probabilities and upper quartiles for the studentized range Appl. Statist. 32(2) 204–210
Montgomery D C (1984) Design and Analysis of Experiments Wiley
Winer B J (1970) Statistical Principles in Experimental Design McGraw–Hill
Error Indicators and Warnings
Note: g01fm may return useful information for one or more of the following detected errors or warnings.
Errors or warnings detected by the method:
If on exit , then g01fm returns .
On entry, , or , or , or .
- The method was unable to find an upper bound for the value of . This will be caused by being too close to .
- There is some doubt as to whether full accuracy has been achieved. The returned value should be a reasonable estimate of the true value.
Accuracy
The returned solution, , to equation (1) is determined so that at least one of the following criteria apply.
(a) | |
(b) | . |
Parallelism and Performance
None.
Further Comments
To obtain the factors for Duncan's multiple-range test, equation (1) has to be solved for , where , so on input p should be set to .
Example
Three values of , and are read in and the Studentized range deviates or quantiles are computed and printed.
Example program (C#): g01fme.cs