SAS/ETS

SAS/ETS® Software: Model, forecast and simulate processes with econometric and time series analysis. Economic and market conditions, customer demographics, pricing and marketing activities can all affect your organization. Our econometric capabilities, time series analysis and time series forecasting techniques can help you understand those factors and improve your strategic planning.


References in zbMATH (referenced in 26 articles , 1 standard article )

Showing results 1 to 20 of 26.
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  1. Chanialidis, Charalampos; Evers, Ludger; Neocleous, Tereza; Nobile, Agostino: Efficient Bayesian inference for COM-Poisson regression models (2018)
  2. Marra, Giampiero; Radice, Rosalba: A joint regression modeling framework for analyzing bivariate binary data in (\mathsfR) (2017)
  3. Bowden, Ross S.; Clarke, Brenton R.: A single series representation of multiple independent ARMA processes (2012)
  4. Abdelaal, Medhat M. A.; Aziz, Essam Fawzy: Using VARIMA model to predict average monthly temperature in Cairo governorate, Egypt (2011)
  5. Al Wadi, S.; Ismail, Mohd Tahir; Alkhahazaleh, M. H.; Karim, Samsul Ariffin Abdul: Selecting wavelet transforms model in forecasting financial time series data based on ARIMA model (2011)
  6. Rajesh Selukar: State Space Modeling Using SAS (2011) not zbMATH
  7. Shetty, Veena; Morrell, Christopher H.; Najjar, Samer S.: Modeling a cross-sectional response variable with longitudinal predictors: an example of pulse pressure and pulse wave velocity (2009)
  8. Fu, Lei; Soh, Leen-Kiat; Samal, Ashok: Techniques for computing Fitness of Use (FoU) for time series datasets with applications in the geospatial domain (2008) ioport
  9. Jones, M. C.; Park, Heungsun; Shin, Key-Il; Vines, S. K.; Jeong, Seok-Oh: Relative error prediction via kernel regression smoothers (2008)
  10. Silberhorn, Nadja; Boztuğ, Yasemin; Hildebrandt, Lutz: Estimation with the nested logit model: specifications and software particularities (2008)
  11. Tsangari, Haritini: An alternative methodology for combining different forecasting models (2007)
  12. Kuss, Oliver: On the estimation of the stereotype regression model (2006)
  13. Ooms, Marius; Doomik, Jurgen A.: Econometric software development: past, present and future (2006)
  14. Park, Heungsun; Shin, Key-Il: A shrinked forecast in stationary processes favouring percentage error (2006)
  15. Li, Siu-Hang; Chan, Wai-Sum: Outlier analysis and mortality forecasting: the United Kingdom and Scandinavian countries (2005)
  16. Chan, W. S.; Cheung, S. H.; Wu, K. H.: Multiple forecasts with autoregressive time series models: Case studies. (2004)
  17. Ellis, Suria; Steyn, Faans; Venter, Hennie: Fitting a Pareto-Normal-Pareto distribution to the residuals of financial data (2003)
  18. Mckenzie, C. R.; Kapuscinski, C. A.: Estimation in a linear model with serially correlated errors when observations are missing (1997)
  19. Tung, Y.-K.; Yeh, K.-C.; Yang, J.-C.: Regionalization of unit hydrograph parameters. I: Comparison of regression analysis techniques (1997)
  20. Venugopalan, R.; Prajneshu: A generalized allometric model for determining length-weight relationship (1997)

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