XYZ 3D Scatter Plot in Excel using BESH Stat

Excel doesn’t offer a built-in 3D scatter plot. It do offer a 3D line chart (multiple line series presented side by side) but that cannot be easily adapted to scatter plot unless one of the variables is  integer with only handful of distinct values. Recently I discovered a Gabor’s Doka the 3D scatter plot for MS Excel, an excel spreadsheet with built-in formulas and macros that offers 3D scatter plot functionality. It offers more-or-less all functionality I wanted so I decided to took the logic from Gabor’s workbook, transformed it into a pure VBA code without any excel formulas; and have it as a more user-friendly version available in BESH Stat add-in starting from version 0.22. Continue reading “XYZ 3D Scatter Plot in Excel using BESH Stat”

Negative Binomial Regression model (NB2)

Negative binomial regression is used for modeling count variables, usually for over-dispersed count outcome variables (e.g. accounting for the extra-Poisson variation). BESH Stats fits negative binomial regression with the traditional NB2[1] parametrization Continue reading “Negative Binomial Regression model (NB2)”

Poisson regression (Generalized linear model GLM)

Poisson regression is fundamental to the modeling of count data. It is the simplest count regression model; and similar to regular multiple linear regression except that the dependent variable is an observed count that follows the Poisson distribution. Continue reading “Poisson regression (Generalized linear model GLM)”

BESH Stat version 0.18 released

I’m happy to announce the release of new BESH Stat version 0.18. The main change is the implementation of Zero-Inflated Poisson regression as described by Diane Lambert in [1]. BESH Stat results on default settings match on 4 decimal place to the R pscl package zeroinfl function parameter estimates and standard errors (by decreasing the convergence criterion on the Settings tab you can increase precision of the estimates) Continue reading “BESH Stat version 0.18 released”

BESH Stat version 0.17 released

I’m happy to announce the release of new BESH Stat version 0.17. The main change is the addition of exact p-value computation for the unordered R x C contingency tables (Fisher-Freeman-Halton Exact test). I was working on this on-and-off for several years now.  The new procedure implements the network algorithm developed by Mehta and Patel [1,2,3] and improved by Clarkson, Fan and Joe [4]. It is a VBA translation of the FORTRAN subroutine FEXACT. The original FORTRAN code can be obtained from [5] (Fortran 77 version) or [6] (Fortran 90 version). To my knowledge this is the only VBA implementation of this method. Generated P-values match those presented in all example tables from [4] and all are computed in a fraction of a second. Continue reading “BESH Stat version 0.17 released”