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NAG[g05lnc] NAG[nag_rngs_logistic] - Generates a vector of random numbers from a logistic distribution, seeds and generator number passed explicitly
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Calling Sequence
g05lnc(a, b, n, x, igen, iseed, 'fail'=fail)
nag_rngs_logistic(. . .)
Parameters
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a - float;
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On entry: , the mean of the distribution.
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b - float;
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On entry: , the spread of the distribution, where "spread" is standard deviation.
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Constraint: . .
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n - integer;
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On entry: , the number of pseudo-random numbers to be generated.
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Constraint: . .
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x - Vector(1..dim, datatype=float[8]);
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Note: the dimension, dim, of the array x must be at least .
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On exit: the pseudo-random numbers from the specified logistic distribution.
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iseed - Vector(1.., datatype=integer[kernelopts('wordsize')/8]);
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On entry: contains values which define the current state of the selected generator.
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On exit: contains updated values defining the new state of the selected generator.
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'fail'=fail - table; (optional)
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The NAG error argument, see the documentation for NagError.
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Description
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Purpose
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nag_rngs_logistic (g05lnc) generates a vector of pseudo-random numbers from a logistic distribution with mean and spread .
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Description
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The distribution has PDF (probability density function)
nag_rngs_logistic (g05lnc) returns the value
where is a pseudo-random number uniformly distributed over .
One of the initialization functions g05kbc (nag_rngs_init_repeatable) (for a repeatable sequence if computed sequentially) or g05kcc (nag_rngs_init_nonrepeatable) (for a non-repeatable sequence) must be called prior to the first call to nag_rngs_logistic (g05lnc).
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Error Indicators and Warnings
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"NE_BAD_PARAM"
On entry, argument had an illegal value.
"NE_INT"
On entry, . Constraint: .
"NE_INTERNAL_ERROR"
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please consult NAG for assistance.
"NE_REAL"
On entry, . Constraint: .
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Examples
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>
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a := 1:
b := 2:
n := 5:
igen := 1:
x := Vector(5, datatype=float[8]):
iseed := Vector([1762543, 9324783, 42344, 742355], datatype=integer[kernelopts('wordsize')/8]):
NAG:-g05lnc(a, b, n, x, igen, iseed):
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