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  2. Stepwise regression - Wikipedia

    en.wikipedia.org/wiki/Stepwise_regression

    The main approaches for stepwise regression are: Forward selection, which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically significant improvement of the fit, and repeating this process until none improves the model to a statistically significant ...

  3. RATS (software) - Wikipedia

    en.wikipedia.org/wiki/RATS_(software)

    The following is a list of the major procedures in econometrics and time series analysis that can be implemented in RATS. All these methods can be used in order to forecast, as well as to conduct data analysis. In addition, RATS can handle cross-sectional and panel data: Linear regression, including stepwise.

  4. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score (), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. [6]

  5. SAS language - Wikipedia

    en.wikipedia.org/wiki/SAS_language

    The SAS language is a fourth-generation computer programming language used for statistical analysis, created by Anthony James Barr at North Carolina State University. [ 1 ] [ 2 ] Its primary applications include data mining and machine learning .

  6. SAS (software) - Wikipedia

    en.wikipedia.org/wiki/SAS_(software)

    SAS Enterprise Guide is SAS's point-and-click interface. It generates code to manipulate data or perform analysis without the use of the SAS programming language. [10] The SAS software suite has more than 200 add-on packages, sometimes called components [11] [12] [13] Some of these SAS components, i.e. add on packages to Base SAS include: [3] [14]

  7. Conditional logistic regression - Wikipedia

    en.wikipedia.org/.../Conditional_logistic_regression

    Conditional logistic regression is an extension of logistic regression that allows one to account for stratification and matching. Its main field of application is observational studies and in particular epidemiology. It was devised in 1978 by Norman Breslow, Nicholas Day, Katherine Halvorsen, Ross L. Prentice and C. Sabai. [1]

  8. Comparison of statistical packages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_statistical...

    World Programming: March 2018 () No Proprietary: CLI, GUI: C, Assembler Python, R, SAS and SQL languages WINKS: TexaSoft August 2013 () No Proprietary: GUI: Fortran, Visual Basic XploRe: MD*Tech 2006 () No Proprietary: GUI: Product Developer Latest version Open source Software license Interface Written in Scripting languages

  9. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/.../Multinomial_logistic_regression

    Multinomial logistic regression is known by a variety of other names, including polytomous LR, [2] [3] multiclass LR, softmax regression, multinomial logit (mlogit), the maximum entropy (MaxEnt) classifier, and the conditional maximum entropy model.