JMulTi was originally designed as a tool for certain econometric procedures in time series analysis that are especially difficult to use and that are not available in other packages, like Impulse Response Analysis with bootstrapped confidence intervals for VAR/VEC modelling. Now many other features have been integrated as well to make it possible to convey a comprehensive analysis. Limitations of this software can be overcome by exporting datasets or computation results and use them with other programs. For an overview of the underlying software concept, see the JStatCom page.

This software is also referenced in ORMS.

References in zbMATH (referenced in 34 articles )

Showing results 1 to 20 of 34.
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  1. Beyaztas, Beste H.: Construction of multi-step forecast regions of VAR processes using ordered block bootstrap (2021)
  2. Golosnoy, Vasyl; Seifert, Miriam Isabel: Monitoring mean changes in persistent multivariate time series (2021)
  3. Divisekara, Roshani W.; Nawarathna, Ruwan D.; Nawarathna, Lakshika S.: Forecasting of global market prices of major financial instruments (2020)
  4. Holt, Matthew T.; Teräsvirta, Timo: Global hemispheric temperatures and co-shifting: a vector shifting-mean autoregressive analysis (2020)
  5. Maleki, Mohsen; Wraith, Darren; Mahmoudi, Mohammad R.; Contreras-Reyes, Javier E.: Asymmetric heavy-tailed vector auto-regressive processes with application to financial data (2020)
  6. Hajria, Raja Ben; Khardani, Salah; Raïssi, Hamdi: A power comparison between autocorrelation based tests (2018)
  7. Pravilovic, Sonja; Bilancia, Massimo; Appice, Annalisa; Malerba, Donato: Using multiple time series analysis for geosensor data forecasting (2017)
  8. Fresoli, Diego E.; Ruiz, Esther: The uncertainty of conditional returns, volatilities and correlations in DCC models (2016)
  9. Lütkepohl, Helmut; Milunovich, George: Testing for identification in SVAR-GARCH models (2016)
  10. Addo, Peter Martey; Billio, Monica; Guégan, Dominique: The univariate MT-STAR model and a new linearity and unit root test procedure (2014)
  11. Nguimkeu, Pierre: Improved inference for moving average disturbances in nonlinear regression models (2014)
  12. Safari, Amir: An e-E-insensitive support vector regression machine (2014)
  13. Fasen, Vicky: Statistical estimation of multivariate Ornstein-Uhlenbeck processes and applications to co-integration (2013)
  14. Lütkepohl, Helmut: Reducing confidence bands for simulated impulse responses (2013)
  15. Kauermann, Göran; Teuber, Timo; Flaschel, Peter: Exploring US business cycles with bivariate loops using penalized spline regression (2012)
  16. Kascha, Christian; Trenkler, Carsten: Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order (2011)
  17. Anderson, Gary S.; Kim, Jinill; Yun, Tack: Using a projection method to analyze inflation bias in a micro-founded model (2010)
  18. Allegret, Jean-Pierre; Sand-Zantman, Alain: Modeling the impact of real and financial shocks on Mercosur: The role of the exchange rate regime (2009)
  19. Barbieri, Laura: Panel unit root tests under cross-sectional dependence: an overview (2009)
  20. Trenkler, Carsten: Bootstrapping systems cointegration tests with a prior adjustment for deterministic terms (2009)

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