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 38 articles , 1 standard article )

Showing results 1 to 20 of 38.
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  1. Jan Górecki, Marius Hofert, Martin Holeňa: Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox (2020) not zbMATH
  2. Singhal, Shakshi; Anand, Adarsh; Singh, Ompal: Understanding multi-stage diffusion process in presence of attrition of potential market and related pricing policy (2019)
  3. Chanialidis, Charalampos; Evers, Ludger; Neocleous, Tereza; Nobile, Agostino: Efficient Bayesian inference for COM-Poisson regression models (2018)
  4. Ibrahim, Amr; Fawzy, Essam; Hassan, Ehab: Using VARMA technique to measure the performance quality of E-service-FIFA2014 (2018)
  5. Marra, Giampiero; Radice, Rosalba: A joint regression modeling framework for analyzing bivariate binary data in (\mathsfR) (2017)
  6. Dany, Antoine; Dantony, Emmanuelle; Elsensohn, Mad-Hélénie; Villar, Emmanuel; Couchoud, Cécile; Ecochard, René: Using repeated-prevalence data in multi-state modeling of renal replacement therapy (2015)
  7. Bowden, Ross S.; Clarke, Brenton R.: A single series representation of multiple independent ARMA processes (2012)
  8. Abdelaal, Medhat M. A.; Aziz, Essam Fawzy: Using VARIMA model to predict average monthly temperature in Cairo governorate, Egypt (2011)
  9. 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)
  10. Rajesh Selukar: State Space Modeling Using SAS (2011) not zbMATH
  11. 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)
  12. 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
  13. Jones, M. C.; Park, Heungsun; Shin, Key-Il; Vines, S. K.; Jeong, Seok-Oh: Relative error prediction via kernel regression smoothers (2008)
  14. Silberhorn, Nadja; Boztuğ, Yasemin; Hildebrandt, Lutz: Estimation with the nested logit model: specifications and software particularities (2008)
  15. Tsangari, Haritini: An alternative methodology for combining different forecasting models (2007)
  16. Kuss, Oliver: On the estimation of the stereotype regression model (2006)
  17. Ooms, Marius; Doornik, Jurgen A.: Econometric software development: past, present and future (2006)
  18. Park, Heungsun; Shin, Key-Il: A shrinked forecast in stationary processes favouring percentage error (2006)
  19. Li, Siu-Hang; Chan, Wai-Sum: Outlier analysis and mortality forecasting: the United Kingdom and Scandinavian countries (2005)
  20. Chan, W. S.; Cheung, S. H.; Wu, K. H.: Multiple forecasts with autoregressive time series models: Case studies. (2004)

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