Excel formula for Pearson IV distribution (w. mean, std dev, skew, & kurtosis)

[ddurant100]

Hello Everyone,

What is the excelformula to generate the inverse Pearson IV distribution? I have mean, standarddeviation, skew and kurtosis and I plan to generate random outputs given thosestats. How do I write the formula?

My question is verydirect and simple. I've looked everywhere for an excel equation for the PearsonIV (4) distribution. I've found software and random formulas, but not one I canfigure out how to build in excel. I found and use a great equation for thePearson III (3) (see: Log Pearson type 3 in Excel - Gerg's Net),but not for #4. I could use your help.

Thank you,

Dave

 

[cyrilbrd]

Hi, just curious as I encounter similar conundrum with some statistical analysis.
I take it you are limited to Excel right?
Now R might be the better tool for statistical analysis... But given that you require Excel I believe that GAMMA.DIST(x,alpha,beta,cumulative) might be part of your required answer?

GAMMA.DIST Returns the gamma distribution. You can use this function to study variables that may have a skewed distribution. The gamma distribution is commonly used in queuing analysis.

here too:

The GAMMA.DIST function syntax has the following arguments (argument: A value that provides information to an action, an event, a method, a property, a function, or a procedure.):X Required. The value at which you want to evaluate the distribution.
Alpha Required. A parameter to the distribution.
Beta Required. A parameter to the distribution. If beta = 1, GAMMA.DIST returns the standard gamma distribution.
Cumulative Required. A logical value that determines the form of the function. If cumulative is TRUE, GAMMA.DIST returns the cumulative distribution function; if FALSE, it returns the probability density function.
Remarks
If x, alpha, or beta is nonnumeric, GAMMA.DIST returns the #VALUE! error value.
If x < 0, GAMMA.DIST returns the #NUM! error value.
If alpha ≤ 0 or if beta ≤ 0, GAMMA.DIST returns the #NUM! error value.
For a positive integer n, when alpha = n/2, beta = 2, and cumulative = TRUE, GAMMA.DIST returns (1 - CHISQ.DIST.RT(x)) with n degrees of freedom.
When alpha is a positive integer, GAMMA.DIST is also known as the Erlang distribution.