# Thread: Help with 3D Gaussian Distribution Formula in Excel?

1. ## Help with 3D Gaussian Distribution Formula in Excel?

Hi Everyone,

I am looking for some help! I am not a statistician but use 3 Gaussian distributions in my work which is all Excel based. I currently use the following formula produce a normally distributed 3D shape in Excel that produces the attached surface plot:-

=h*EXP(-1*(a*(Valx0-x0)^2+2*b*(Valx0-x0)*(Valy0-y0)+c*(Valy0-y0)^2))

I use Excel Solver to alter the a,b,c,x0 and y0 to achieve the best fit to the actual data (Pictures attached).

What I would like some help with is how I can alter this formula to add 'skew' in either the x0 or y0 direction so I can get a better fit to the actual shape…..

Any help would be greatly appreciated!

Thank you.

2. ## Re: Help with 3D Gaussian Distribution Formula in Excel?

1. I believe you have a bivariate Gaussian distribution which you plot out the estimated joint density. To estimate the parameter you can use different methods like the MLE which has closed form solution and thus do not need to use numerical solver.

2. Ordinary bivariate Gaussian distribution is symmetric. The marginal distribution of either component is just univariate Gaussian therefore the projection of the joint density in either x or y direction should produce a bell-shaped figure again. Of course due to possible correlation in general it will be an ellipse from top view. And the most important thing is to define "skewness" in multivariate sense.

One can always have different way to generalize the normal distribution, like

http://en.wikipedia.org/wiki/Skew_normal_distribution
http://en.wikipedia.org/wiki/General...l_distribution
http://en.wikipedia.org/wiki/Pearson_distribution

Again it depends on your need.

3. ## Re: Help with 3D Gaussian Distribution Formula in Excel?

Thank you so much for answering my post and pointing me in the right direction.

My understanding of statistics is very limited but I think I can see what to do to alter my formula to put skew into it.

Thanks again.

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