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On the measurability and consistency of minimum contrast estimates

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  1. Vajda, Igor, 1995. "Conditions equivalent to consistency of approximate MLE's for stochastic processes," Stochastic Processes and their Applications, Elsevier, vol. 56(1), pages 35-56, March.
  2. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
  3. Shiqing Ling & Michael McAleer, 2010. "A general asymptotic theory for time‐series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(1), pages 97-111, February.
  4. Douc, R. & Doukhan, P. & Moulines, E., 2013. "Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2620-2647.
  5. P. Gänssler, 1972. "Note on minimum contrast estimates for Markov processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 19(1), pages 115-130, December.
  6. Nicoletta D’Angelo & Marianna Siino & Antonino D’Alessandro & Giada Adelfio, 2022. "Local spatial log-Gaussian Cox processes for seismic data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 633-671, December.
  7. Nicklas Werge & Olivier Wintenberger, 2022. "AdaVol: An Adaptive Recursive Volatility Prediction Method," Post-Print hal-02733439, HAL.
  8. Ao Yuan & Jan G. De Gooijer, 2007. "Semiparametric Regression with Kernel Error Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 841-869, December.
  9. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
  10. Meitz, Mika & Saikkonen, Pentti, 2011. "Parameter Estimation In Nonlinear Ar–Garch Models," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1236-1278, December.
  11. R. Michel, 1973. "The bound in the Berry-Esseen result for minimum contrast estimates," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 20(1), pages 148-155, December.
  12. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
  13. Petr Lachout & Eckhard Liebscher & Silvia Vogel, 2005. "Strong convergence of estimators as ε n -minimisers of optimisation problemsof optimisation problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(2), pages 291-313, June.
  14. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2015. "A Note on “Continuous Invertibility and Stable QML Estimation of the EGARCH(1,1) Model”," Tinbergen Institute Discussion Papers 15-131/III, Tinbergen Institute.
  15. Stelios Arvanitis, 2013. "On the Existence of Strongly Consistent Indirect Estimators When the Binding Function Is Compact Valued," Journal of Mathematics, Hindawi, vol. 2013, pages 1-14, November.
  16. Horst Wegner, 1976. "On the existence of maximum probability estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 28(1), pages 343-347, December.
  17. J. Pfanzagl, 1971. "The Berry-Esseen bound for minimum contrast estimates," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 17(1), pages 82-91, December.
  18. Werge, Nicklas & Wintenberger, Olivier, 2022. "AdaVol: An Adaptive Recursive Volatility Prediction Method," Econometrics and Statistics, Elsevier, vol. 23(C), pages 19-35.
  19. Yan Sun & Dan Ralescu, 2015. "A normal hierarchical model and minimum contrast estimation for random intervals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 313-333, April.
  20. Catania, Leopoldo & Luati, Alessandra, 2020. "Robust estimation of a location parameter with the integrated Hogg function," Statistics & Probability Letters, Elsevier, vol. 164(C).
  21. D'Angelo, Nicoletta & Adelfio, Giada & Mateu, Jorge, 2023. "Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
  22. Sondre Hølleland & Hans Arnfinn Karlsen, 2020. "A Stationary Spatio‐Temporal GARCH Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 177-209, March.
  23. István Berkes & Lajos Horváth & Shiqing Ling, 2009. "Estimation in nonstationary random coefficient autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(4), pages 395-416, July.
  24. Ao Yuan, 2009. "Semiparametric inference with kernel likelihood," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(2), pages 207-228.
  25. Christophe Ange Napoléon Biscio & Frédéric Lavancier, 2017. "Contrast Estimation for Parametric Stationary Determinantal Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 204-229, March.
  26. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
  27. F Blasques & P Gorgi & S J Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models ," Working Papers hal-01377971, HAL.
  28. Mamadou Lamine Diop & William Kengne, 2017. "Testing Parameter Change in General Integer-Valued Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 880-894, November.
  29. Werge, Nicklas & Wintenberger, Olivier, 2022. "AdaVol: An Adaptive Recursive Volatility Prediction Method," Econometrics and Statistics, Elsevier, vol. 23(C), pages 19-35.
  30. W. Sahler, 1970. "Estimation by minimum-discrepancy methods," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 16(1), pages 85-106, December.
  31. Nicklas Werge & Olivier Wintenberger, 2020. "AdaVol: An Adaptive Recursive Volatility Prediction Method," Papers 2006.02077, arXiv.org, revised Jan 2021.
  32. Gang Zheng & Qizhai Li & Ao Yuan, 2014. "Some Statistical Properties of Efficiency Robust Tests with Applications to Genetic Association Studies," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 762-774, September.
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