What's New in GAUSS 17?

Improved Data Handling

Feature plot of wine chemistry variables

Option to specify models and data in terms of model variables:

//Load specified variables in a GAUSS matrix: 
X = loadd("wine_quality.dat", "rating + citric acid + sulphates");
//Estimate parameters of model: 
//rating = α + β1*citric acid + β2*sulphates
call ols("wine_quality.dat", "rating ~ citric acid + sulphates");
//Calculate descriptive statistics on all
//variables in dataset except for 'fixed acidity' and 'chlorides'
call dstatmt("wine_quality.dat", ". -fixed acidity -chlorides");
  • Simple to use
  • Consistent with other statistical packages
  • Well documented
  • Backwards compatible

Compute and estimate CSV, XLSX and HDF5 data directly

Intelligent file handling allows you to use many different file types as data sources for GAUSS procedures:

//Load specified variables from a CSV file to a GAUSS matrix: 
X = loadd("wine_quality.csv", "rating + citric acid + sulphates");
//Estimate parameters of model: 
//rating = α + β1*citric acid + β2*sulphates,
//using data from an Excel file
call ols("wine_quality.xlsx", "rating ~ citric acid + sulphates");
//Calculate descriptive statistics on all variables
//in an Excel file except for 'fixed acidity' and 'chlorides'
call dstatmt("wine_quality.xlsx", ". -fixed acidity -chlorides");

Support for HDF5 datasets provides:

  • Unlimited dataset size
  • Fast data read and write
  • Supported as native GAUSS file type
  • Portable to all operating systems and many software packages

New Graphics Functionality

Plot of 95% confidence interval for normal distribution.
Logistic probability density
Plot of Google stock price with exponential moving average

Support for LaTeX in titles, legends, axis labels and text boxes

//Add LaTeX formula to title
plotSetTitle(&myPlot, "\\Delta y = y_t - y_{t-1}");

Empirical Distribution Plot
Surface plot with plane
Plot of credit limits by age group with error bars
Plot of lasso tune by MSE

New functions:

  • plotAddErrorBar: Create XY plots with user specified symmetrical or asymmetrical error bars
  • plotAddSurface: Adds a surface or plane to an existing surface plot
  • plotSetLegendFont: Controls the font family, size and color of the text in the legend
  • plotCDFEmpirical: Plots the empirical distribution function of an input vector or vectors
Surface plot
Surface plot with viridis color map
Contour plot
Contour plot with 2 peaks

Function enhancements:

  • New color maps for surface and contour plots make it easy to create professional and attractive 3-D graphics
  • Added option to place height on contour lines in plotContour
  • Added option to place colors at specific heights, rather than splitting the colors evenly for surface and contour plots
  • The terminal version of GAUSS, ‘tgauss’, and the GAUSS Engine can now create and save graphs on headless servers

Graphics Editor now allows interactive control of:

  • View angle, lighting and toggle the mesh in surface graphs
  • Extent of range of X and Y axes

New Mathematical and Statistical Functionality

LDL matrix factorization

New functions:

  • cdfEmpirical: Computes the empirical cumulative distribution function
  • ldl: Computes and returns the ‘L’ and ‘D’ factors from a symmetric matrix
  • powerm: Raises a matrix to a specified power
  • sylvester: Calculates the solution to the Sylvester matrix equation
  • rndWishartInv: Takes draws from the Inverse Wishart distribution
  • pdfWishartInv: Computes the probability density function of the inverse Wishart distribution
  • dot: Computes the dot product for a vector or group of vectors

Function Speedups

  • X’X for large matrices is nearly twice as fast
  • sortc is much faster, especially for column vectors
  • Greatly improved speed of unique and uniquesa, especially when operating on string arrays
  • Linear solve, using the slash-operator ‘/’ for small matrices
  • Kronecker product ‘.*.’ is faster when one of the inputs is a column vector
  • crossprd is faster for case of fewer than 500 vectors
  • cdffc is 10-1000x faster when ‘d1’ parameter is equal to one
  • reclassify is much faster and uses less memory

Other Enhancements

Function enhancements:

  • quantile/quantiled: Added option to specify the calculation method
  • glm: Added support for inverse Gaussian family and models without intercepts when estimating the parameters of the General Linear Model
  • schur: Added support for immediate return of complex form
  • Improved tree view of data on the Data Page
  • getorders and getdims now support matrices, strings and string arrays
  • strsplit now supports multi-character delimiters
  • New function strtrim removes white-space from the left and right side of a string or each element of a string array
  • Bug fixes and more…

GAUSS HPCC

GAUSS HPCC (High Performance Cluster Computing) boosts the computing power of GAUSS, harnessing the capabilities of high speed cluster machines, for incredible speed and performance.

Built-in, efficient cluster computing support:

  • Create high-level GAUSS programs that use the fast, low-level MPI library
  • A version of GAUSS HPCC will be made available to Universities who own a Floating Network license with current Platinum Premier Support & Maintenance at no extra charge

Builds on these features included in the standard version of GAUSS 17:

  • Compatible with Hadoop:
    - Easily create GAUSS mapper and reducer functions
  • Connect to NoSQL and Big Data databases such as:
    - MongoDB, Hbase, Hive, Pig and more
  • Support for streaming or online algorithms for data that does not fit entirely in memory.

Quick instantiation with a small memory footprint allows for high performance across the cluster

Recent Upgrades of GAUSS

If you are upgrading from earlier versions of GAUSS, GAUSS 17 allows users to enjoy many years worth of program advances and new features such as those included in recent releases of GAUSS:

- GAUSS 13
- GAUSS 14
- GAUSS 15
- GAUSS 16