GAUSS is an easy-to-use data analysis, mathematical and statistical environment based on the powerful, fast and efficient GAUSS Matrix Programming Language. GAUSS has been used by leaders in data-dependent fields at major institutions for more than 30 years. Get a complete analysis environment with the built-in tools you need for estimation, forecasting, simulation, visualization and more
- Fully customizable
GAUSS allows you to stay ahead of the curve by giving you the tools you need to modify our algorithms or create the latest and greatest from the ground up. - Interactive and fast
A fully interactive environment for exploring data, performing calculations and analyzing results. The exceptionally fast GAUSS analytics engine will speed up your computations. - Visualization and presentation
Intuitive and powerful interactive and programmatic methods make it easy to create beautiful and professional 2D and 3D graphics to analyze your data and present your findings.
Info
What is GAUSS?
An Introduction to GAUSS
The GAUSS Platform is an interactive environment designed for math and statistics, which has been used by leaders in data-dependent fields at major institutions for more than 30 years.
Comprehensive Environment for Modeling and Analysis
The GAUSS base platform is a complete analysis environment with the built-in tools you need for estimation, forecasting, simulation, visualization and more.
It allows you to stay ahead of the curve by giving you the tools you need to modify our algorithms or create the latest and greatest from the ground up.
The GAUSS Platform provides a fully interactive environment for exploring data, performing calculations and analyzing results. These interactive features speed up your workflow, while the exceptionally fast analytics engine will speed up your computations.

The GAUSS analytics engine has been designed to be extremely lightweight and efficient while making the most use of your hardware. From a small laptop to a large cluster, nothing scales as well as GAUSS.
Intuitive and powerful interactive and programmatic methods make it easy to create beautiful and professional 2D and 3D graphics to analyze your data and present your findings. Your high-resolution GAUSS graphics can be exported to many popular formats such as PNG, PDF, SVG, TIFF and more.

Uutta
New features in GAUSS 23
GAUSS 23 is the latest and most user-friendly version of GAUSS, designed to streamline your research process by making it easier to find, import, and model data.
Data at Your Fingertips

Load Data from Anywhere on the Internet
// Load an Excel file from the aptech website
file_url = “http://www.aptech.com/wp-content/uploads/2019/03/skincancer2.xlsx”;
skin_cancer = loadd(file_url);
// Print the first 5 rows of the dataframe
head(skin_cancer);

Simplified Data Loading with…
Automatic Type Detection
Previous versions required formula strings with keywords to specify date, string, and categorical variables from some file types.

Smart data type detection in GAUSS 23 figures out the variable type so you do not have to specify it manually. Automatically detects nearly 40 popular date formats.

Automatic Header and Delimiter Detection
Replace old code like this:
load X[127,4] = mydata.txt;
with
X = loadd(“mydata.txt”);
Automatically handles:
First-Class Dataframe Storage

No new code to learn, use the .gdat file extension with loadd and saved to load and store your dataframes.
Expanded Quantile Regressions

hitters = loadd(“islr_hitters.xlsx”);
tau = 0.90;
call quantileFit(hitters, “ln(salary) ~ AtBat + Hits + HmRun”, tau);

Kernel Density Estimations

Improved Covariance Computations
// Load data
fname = getGAUSShome(“examples/auto2.dta”);
auto = loadd(fname);
// Declare control structure
struct olsmtControl ctl;
ctl = olsmtControlCreate();
// Turn on residuals
ctl.res = 1;
// Turn on HAC errors
ctl.cov = “hac”;
call olsmt(auto, “mpg ~ weight + foreign”, ctl);

New Functions for Data Cleaning and Exploration
between
Returns a binary vector indicating which observations fall in a specified range. It can be used with selif to select rows. Dates and ordinal categorical columns are supported.
// Return a 1 if the observation is between the listed dates
match = between(unemp[.,”DATE”], “2020-03”, “2020-08”);
// Select the matching observations
unemp = selif(unemp, match);

where
Provides a convenient and intuitive way to combine or modify data. It returns elements from either a or b depending upon condition.
// Daily hotel room price
hotel_price = { 238, 405, 405, 329, 238 };
// Daily temperature forecast
temperature = { 89, 94, 110, 103, 97 };
// Decrease the price by 10% if the
// temperature will be more than 100 degrees
new_price = where(temperature .> 100,
hotel_price .* 0.9,
hotel_price);
new_price = 238 405 364.50 296.10 238
Speed-ups and Efficiency Improvements
For a complete list of all GAUSS 23 offers please see the complete changelog.
New features in GAUSS 22
GAUSS 22 brings many substantial new features that will save you hours of time and frustration with everyday tasks like:
See some of the ways that will help you make the most of your limited research time below!
Intelligent Graph Attributes

GAUSS highlight’s Important Parts of Your Data


Simple Data Filtering with Strings and Dates

Easily Generate New Variables

Clean Messy Data with GAUSS

Aggregate by String, Category or Date

- Options for how to handle missing values.
Simple Data Merge

- Load and combine data from CSV, Excel, SAS, Stata, SPSS.
Changelog
GAUSS 22 has more new features and bug fixes than any previous version. For a complete list of what’s new, see the complete changelog.
Ohjelmanvaatimukset
System requirements for GAUSS
Lisensointi
Lisenssivaihtoehdot
Tuki
Tuki
For technical support, please contact Software Support!
Please include your serial number with all email correspondence.
Kuvaile ongelmasi mahdollisimman yksityiskohtaisesti, kun otat yhteyttä tukeemme. Muista aina ilmoittaa sarja-/lisenssinumerosi, tuoteversiosi ja käyttöjärjestelmäsistem.
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