KITCHENER, Ontario, March 15, 2022 (GLOBE NEWSWIRE) -- SigmaXL Inc., a leading provider of user-friendly Excel Add-ins for Statistical and Graphical analysis, announces the release of SigmaXL Version 9.1.
“SigmaXL was designed from the ground up to be a cost-effective, powerful, but easy to use tool that enables users to measure, analyze, improve and control their service, transactional, and manufacturing processes. As an add-in to the already familiar Microsoft Excel, SigmaXL is ideal for Lean Six Sigma training or use in a college statistics course. Version 9.1 adds Advanced Multiple Regression capabilities,” said John Noguera, CTO, SigmaXL.
New features in Version 9.1 include:
Advanced Multiple Regression > Fit Multiple Regression Model
- Standardization and coding of continuous predictors
- Option to display regression equation with unstandardized coefficients
- (1, 0) or (-1, 0, +1) coding of categorical predictors
- Box-Cox Transformation
- Specify confidence level
- Residual Plots: Regular, Standardized and Studentized – Deleted t
- Diagnostic measures: Cook's Distance (Influence), Leverage and DFITS
- Storage of model design matrix
- Main Effects and Interaction Plots (Fitted Means)
- Contour and Surface Plots
- Optimization with optional constraints including integer continuous
- Automatic removal of extreme VIF or collinear terms (with alias and removal report)
- Specify interactions, quadratic and higher orders (all interactions or up to 3-Way)
- ANOVA Type I and/or Type III Sum-of-Squares with Pareto of Percent Contribution and Standardized Effects
- Lenth Pseudo Standard Error for Saturated Models with Monte Carlo or Student T P-Values
- Specify Test/Withhold Sample for R-square Test & StDev Test Validation
- R-Square Predicted (Leave-One-Out Cross Validation)
- R-Square K-Fold & StDev K-Fold (K-Fold Cross Validation)
- Test for Constant Variance: Breusch-Pagan Normal or Koenker (Robust)
- White robust standard errors for non-constant variance
- Durbin-Watson test for autocorrelation in residuals with P-Values
- Newey-West robust standard errors for non-constant variance with autocorrelation
- White or Newey-West automatically selected based on Durbin-Watson P-Values
- Stepwise/Best Subsets Regression:
- Forward/Backward with alpha-to-enter, alpha-to-remove
- Forward Selection with alpha-to-enter
- Backward Elimination with alpha-to-remove
- Forward, Backward Criterion: Minimize AICc, BIC; Maximize R-Square Adjusted, R-Square Predicted, R-Square K-Fold
- Best Subsets utilizes the powerful MIDACO Solver (Mixed Integer Distributed Ant Colony Optimization) to solve best subsets with up to hundreds of continuous or categorical variables, including interactions and higher order terms. This feature gives SigmaXL a significant advantage over competitors with Best Subsets limited to 30 continuous variables.
- Best Subsets Criterion: Minimize AICc, BIC; Maximize R-Square Adjusted
- Hierarchical option
- Detailed report with additional statistics such as Condition Number and Mallows’ Cp.
Advanced Multiple Regression > Multiple Response Optimization
- Multiple Response Optimization with Desirability
- Multistart Nelder-Mead Simplex
- MIDACO
Help > What Graphical Tool should I use?
- Summary of SigmaXL Graphical Tools
Help > What Statistical Tool should I use?
- Summary of SigmaXL Graphical Tools
A free 30-day trial version is available for download from the SigmaXL website at: www.SigmaXL.com.
About SigmaXL Inc.
SigmaXL is a leading provider of user-friendly Excel Add-ins for Lean Six Sigma tools and Monte Carlo Simulation. SigmaXL customers include market leaders like DHL, FedEx, Hanes, Kimberly-Clark, Motorola, NASA, Sonoco, Southwest Airlines and Western Union. SigmaXL software is also used by numerous colleges, universities and government agencies.
For more information, visit http://www.SigmaXL.com or call 1-888-SigmaXL (888-744-6295).
Press Contact: Diane Tilley (888) 744-6295
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/9c5533e9-28c0-4370-951b-2145eb4c9703
