GAUSS 18

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Increase your productivity with GAUSS 18

Move from data to results more efficiently than ever with GAUSS 18. New features improve data reading and handling capabilities, expand built-in analytical and graphic tools and significantly increase computation speeds. Learn more about how you can accomplish more with the most powerful GAUSS version yet! [/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row css=".vc_custom_1509112454223{padding-top: 0px !important;padding-bottom: 0px !important;background-color: #455560 !important;}" el_class="sectiongray"][vc_column css=".vc_custom_1509112386042{padding-top: 0px !important;padding-bottom: 0px !important;}"][vc_row_inner el_class="wp-center request-a-quote-section"][vc_column_inner el_class="unit w-1-2 left" width="1/2"][vc_column_text]

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Improved data handling

Load, transform and analyze in one line. Simple to use formula string notation supports:
  • Categorical and dummy variables
  • Data transformations (ln, exp and more)
  • SAS and Stata datasets
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Generalized Method of Moments (GMM)

New GAUSS 18 GMM procedures estimate parameters from custom user specified moment equations or analytic instrumental variables estimates using one step, two-step, iterative, or continuously updating GMM.
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Graphics updates

Convey insights from your data with modern, professional images.
  • 30+ built-in color palettes, and custom palettes
  • Programmatic canvas sizing
  • Added 2-D plot flexibility and options
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New functions to increase productivity

Uncover data insights quicker with new tools for searching matrices and string arrays, reorganizing, merging, and much more!
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Speed improvements

• Chained concatenation operations 2-4x faster • X’Y for vector-vector case 15%-600% faster • Descriptive statistics and OLS 15-30% faster for medium to large matrices
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New mathematical functions

besselk computes the modified Bessel function of the second kind; useful for the negative inverse gaussian distribution. • rndRayleigh to compute Rayleigh distributed random numbers. • gmmFit and gmmFitIV for estimation using the generalized method of moments. • cdfTruncNorm, pdfTruncNorm, cdfLogNorm and pdfLogNorm. • Optional mu, and sigma inputs for cdfn and pdfn • Array support for erf, erfc, erfcinv, erfc, pdfn, power op.
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