Description: The parameter of the distribution, lambda, is equal to one divided by the average time between events. The times between successive events are described by an exponential distribution.
Definition: Using xp := XRange( 0, -Ln(epsilon)/lambda) do Probdist(Exponential_pdf(Lambda,xp),xp)
Description: c and k are the scale and shape of the distribution
Definition: Using xp := XRange( c*(-Ln(1-epsilon))^(1/k), c*(-Ln(epsilon))^(1/k) ) do Probdist(Weibull_pdf(C, K,xp),xp)
Location: 320,48
Nodesize: 48,20
Paramnames: C, K
Function Logistic(mu,alpha)
Title: Logistic~
(mu, alpha)
Description: mu and alpha are the mean and scale of the distribution
Definition: Using xp := XRange( mu-alpha*Ln(1/epsilon - 1), mu-alpha*Ln(1/(1-epsilon)-1)) do Probdist(Logistic_pdf(mu, alpha,xp),xp)
Location: 200,48
Nodesize: 48,20
Paramnames: Mu, Alpha
Function Gamma(lambda,k)
Title: Gamma~
(lambda, k)
Description: lambda and k are the scale and shape of the distribution
Definition: Using xp := XRange( 0, 10/lambda ) do Probdist(Gamma_pdf(Lambda, K,xp),xp)
Location: 200,104
Nodesize: 48,20
Paramnames: Lambda, K
Function Erf(h)
Title: Error Function~
(h)
Description: h is the variance parameter
Definition: Using xp := XRange( -3/h, 3/h) do Probdist(Error_func(H,xp),xp)
Location: 80,104
Nodesize: 48,20
Paramnames: H
Model Support
Title: support
Description: Infrastructure to support the distribution functions, including the functional forms of the PDFs and x-axis indexing.
Location: 320,176
Nodesize: 48,20
Diagstate: 1,344,354,328,213,1
Model The_pdfs
Title: the PDFs
Description: The probability density functions for the distributions. These are used in calculating the distributions.
Author: Brian Sterling
Date: Mon, Feb 28, 1994 10:47 PM
Location: 128,160
Nodesize: 48,20
Diagstate: 1,563,45,193,288,1
Function Exponential_pdf(lambda,x)
Title: Exponential_Pdf~
( lambda, x )
Description: The parameter of the distribution, lambda, is equal to one divided by the average time between events. The times between successive events are described by an exponential distribution.
Definition: if x<= 0 then 0 else lambda*exp(-lambda*x)
Location: 72,40
Nodesize: 52,20
Paramnames: Lambda, X
Function Weibull_pdf(c,k,x)
Title: Weibull_Pdf~
( c, k, x )
Description: c and k are the scale and shape of the distribution
Definition: if k>1 then (k/c)*(x/c)^(k-1)*exp(-((x/c)^k)) else Exponential_pdf( 1/c, x )
Location: 72,152
Nodesize: 52,20
Paramnames: C, K, X
Function Logistic_pdf(mu,alpha,x)
Title: Logistic_Pdf~
( mu, alpha, x )
Description: mu and alpha are the mean and scale of the distribution
Description: lambda and k are the scale and shape of the distribution
Definition: if k>1 then lambda^k*x^(k-1)*exp(-lambda*x) else Exponential_pdf(lambda,x)
Location: 72,264
Nodesize: 52,20
Paramnames: Lambda, K, X
Function Error_func(h,x)
Title: Error_Func~
( h, x )
Description: h is the variance parameter
Definition: exp(-(h^2)*(x^2))
Location: 72,208
Nodesize: 52,20
Paramnames: H, X
Close The_pdfs
Function Xrange(a,b)
Title: XRange
Description: XRange creates a sequence of numbers from a to b and makes this sequence indexed by DummyX so that it can be used in the definitions of functions.
Definition: array( dummyx, sequence( a, b, (b-a)/sampleres))
Location: 200,104
Nodesize: 48,20
Paramnames: A, B
Index Dummyx
Title: DummyX
Description: DummyX is a placeholder index that is used to associate X and Y Pdf values.
Definition: sequence( 0, sampleres )
Location: 80,104
Nodesize: 48,20
Constant Sampleres
Title: Sample~
Resolution
Description: Sample resolution is the number of data points needed for accurate interpolation of Pdf curves used in generating user-defined distribution functions.
Definition: 300
Location: 200,40
Nodesize: 48,20
Constant Epsilon
Title: epsilon
Description: Determines the cutoffs of the tails. The distributions are cutoff at the x-values where the CDF is epsilon and 1-epsilon.~
~
Exponential, Logistic, and Weibull use this constant.