Aptech Module – Linear Regression MT

Linear Regression MT

Dieses Modul ist ein Satz von Prozeduren zur Abschätzung von einzelnen Gleichungen oder eines gleichmäßig verteilten Systems von Gleichungen mittels OLS. Es ermöglicht Randbedingungen für Koeffizienten, berechnet den het-con Standardfehler sowie die minimierten quadratischen Fehler. Linear Regression MT ist multithreadfähig und verwendet Strukturen.

Spezielle Features

  • Berechnungen von Klein Modellen nach der 3-Stufen kleinste Quadrat-Methode
  • lineare Kostenteilungsmodelle
  • beziehungslose Regressionen
  • Tests auf strukturelle Veränderungen
  • Tests auf Heteroskedastizität
  • Erstellung von Vertrauensbereichen für Betaschätzungen
  • Überprüfungen auf Kolinearitäten

Details:

The Linear Regression MT application module is a set of procedures for estimating single equations or a simultaneous system of equations. It allows constraints on coefficients, calculates het-con standard errors, and includes two-stage least squares, three-stage least squares, and seemingly unrelated regression.

Features

  • Calculates heteroskedastic-consistent standard errors, and performs both influence and collinearity diagnostics inside the ordinary least squares routine (OLS)

  • All regression procedures can be run at a specified data range

  • Performs multiple linear hypothesis testing with any form

  • Estimates regressions with linear restrictions

  • Accommodates large data sets with multiple variables

  • Stores all important test statistics and estimated coefficients in an
    efficient manner

  • Both three-stage least squares and seemingly unrelated regression can be
    estimated iteratively

  • Thorough Documentation

  • The comprehensive user's guide includes both a well-written tutorial and an informative reference section. Additional topics are included to enrich the usage of the procedures. These include:

    • Joint confidence region for beta estimates

    • Tests for heteroskedasticity

    • Tests of structural change

    • Using ordinary least squares to estimate a translog cost function

    • Using seemingly unrelated regression to estimate a system of cost share equations

    • Using three-stage least squares to estimate Klein's Model I

Platform: Windows, Mac, Linux and Solaris.

Requirements: GAUSS/GAUSS Light version 8.0 or higher.

 

 

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