SHAZAM is powerfully simple software for econometricians, statisticians, biometricians, sociometricians, psychometricians, politicometricians and all others who analyze data. SHAZAM makes complex techniques simple so you can focus on the problem, not the mechanics SHAZAM combines an easy to use Command Language with a Point-and-Click interface for reusable analysis SHAZAM is reliable, peer reviewed software used worldwide for more than 30 years in Education, Research, Government and Industry SHAZAM is well suited for numerous applications from the specification and estimation of complex models of economic behaviour to Monte Carlo simulation studies for assessing the statistical properties of test statistics SHAZAM comes with fast, responsive and FREE technical support

References in zbMATH (referenced in 30 articles )

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  1. Marek Hlavac: ExtremeBounds: Extreme Bounds Analysis in R (2016)
  2. Yalta, A.Talha; Yalta, A.Yasemin: Should economists use open source software for doing research? (2010) ioport
  3. Renfro, Charles G.: The practice of econometric theory. An examination of the characteristics of econometric computation (2009)
  4. Albertson, K.; Aylen, J.; Lim, K.B.: The power of the Durbin Watson test when the errors are PAR(1) (2002)
  5. Draeseke, Robert; Giles, David E.A.: A fuzzy logic approach to modelling the New Zealand underground economy (2002)
  6. Yamamoto, Yoshikazu; Nakano, Junji: Distributed processing functions of a time series analysis system (2002)
  7. Yamamoto, Yoshikazu; Nakano, Junji; Fujiwara, Takeshi; Kobayashi, Ikunori: A mixed user interface for a statistical system (2002)
  8. Chaturvedi, Anoop; Wan, Alan T.K.; Singh, Shri P.: Stein-rule restricted regression estimator in a linear regression model with nonspherical disturbances (2001)
  9. Östermark, Ralf: Genetic modelling of multivariate EGARCHX-processes: evidence on the international asset return signal response mechanism (2001)
  10. Matthews, Peter Hans: An econometric model of the circuit of capital (2000)
  11. Vougas, Dimitrios V.: A comparison of LS/ML and GMM estimation in a simple AR(1) model (2000)
  12. Skeels, Christopher L.; Vella, Francis: A Monte Carlo investigation of the sampling behavior of conditional moment tests in Tobit and probit models (1999)
  13. Baltagi, Badi H.: Econometrics (1998)
  14. Baltagi, Badi H.: Solutions manual for \itEconometrics (1998)
  15. Coelli, Tim; Prasada Rao, D.S.; Battese, George E.: An introduction to efficiency and productivity analysis (1998)
  16. McKenzie, C.R.: The properties of some two step estimators of ARMA models. (1997) ioport
  17. McKenzie, C.R.: The properties of some two-step estimators of ARMA models. (1997) ioport
  18. Mckenzie, C.R.; Kapuscinski, C.A.: Estimation in a linear model with serially correlated errors when observations are missing (1997)
  19. Giles, Judith A.; Giles, David E.A.: Risk of a homoscedasticity pre-test estimator of the regression scale under LINEX loss (1996)
  20. Golan, Amos; Judge, George; Miller, Douglas: Maximum entropy econometrics: robust estimation with limited data (1996)

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