IDEAS home Printed from https://ideas.repec.org/r/eee/jmvana/v9y1979i3p343-361.html

Strong consistency of least squares estimates in multiple regression II

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Marie Chiron & Jérôme Morio & Sylvain Dubreuil, 2023. "Local Sensitivity of Failure Probability through Polynomial Regression and Importance Sampling," Mathematics, MDPI, vol. 11(20), pages 1-19, October.
  2. Kuo-Hao Chang & L. Jeff Hong & Hong Wan, 2013. "Stochastic Trust-Region Response-Surface Method (STRONG)---A New Response-Surface Framework for Simulation Optimization," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 230-243, May.
  3. Yuan-chin Chang, 2011. "Sequential estimation in generalized linear models when covariates are subject to errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 93-120, January.
  4. Cohen, Guy & Francos, Joseph M., 2002. "Linear Least Squares Estimation of Regression Models for Two-Dimensional Random Fields," Journal of Multivariate Analysis, Elsevier, vol. 82(2), pages 431-444, August.
  5. Zimu Chen & Zhanfeng Wang & Yuan‐chin Ivan Chang, 2020. "Sequential adaptive variables and subject selection for GEE methods," Biometrics, The International Biometric Society, vol. 76(2), pages 496-507, June.
  6. Lita da Silva, João, 2014. "Some strong consistency results in stochastic regression," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 220-226.
  7. Krätschmer, Volker, 2006. "Strong consistency of least-squares estimation in linear regression models with vague concepts," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 633-654, March.
  8. Yong Tao & Xiangjun Wu & Tao Zhou & Weibo Yan & Yanyuxiang Huang & Han Yu & Benedict Mondal & Victor M. Yakovenko, 2019. "Exponential structure of income inequality: evidence from 67 countries," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 345-376, June.
  9. Li, Gaorong & Feng, Sanying & Peng, Heng, 2011. "A profile-type smoothed score function for a varying coefficient partially linear model," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 372-385, February.
  10. R. M. Balan & Ioana Schiopu-Kratina, 2004. "Asymptotic Results with Generalized Estimating Equations for Longitudinal data II," RePAd Working Paper Series lrsp-TRS398, Département des sciences administratives, UQO.
  11. Jin Zhang, 2020. "Consistency of MLE, LSE and M-estimation under mild conditions," Statistical Papers, Springer, vol. 61(1), pages 189-199, February.
  12. Eck, Daniel J., 2018. "Bootstrapping for multivariate linear regression models," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 141-149.
  13. David Rossell & Donatello Telesca, 2017. "Nonlocal Priors for High-Dimensional Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 254-265, January.
  14. Wu, Tiee-Jian & Wasan, M. T., 1996. "Weighted least squares estimates in linear regression models for processes with uncorrelated increments," Stochastic Processes and their Applications, Elsevier, vol. 64(2), pages 273-286, November.
  15. Norbert Christopeit & Michael Massmann, 2013. "A Note on an Estimation Problem in Models with Adaptive Learning," Tinbergen Institute Discussion Papers 13-151/III, Tinbergen Institute.
  16. Norbert Christopeit & Michael Massmann, 2012. "Strong Consistency of the Least-Squares Estimator in Simple Regression Models with Stochastic Regressors," Tinbergen Institute Discussion Papers 12-109/III, Tinbergen Institute.
  17. Zhou, Xian & You, Jinhong, 2004. "Wavelet estimation in varying-coefficient partially linear regression models," Statistics & Probability Letters, Elsevier, vol. 68(1), pages 91-104, June.
  18. Norbert Christopeit & Michael Massmann, 2010. "Consistent Estimation of Structural Parameters in Regression Models with Adaptive Learning," Tinbergen Institute Discussion Papers 10-077/4, Tinbergen Institute.
  19. Guo-Liang Fan & Han-Ying Liang & Jiang-Feng Wang & Hong-Xia Xu, 2010. "Asymptotic properties for LS estimators in EV regression model with dependent errors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(1), pages 89-103, March.
  20. Robin C. O. Palmberg & Yusak O. Susilo & Győző Gidófalvi & Fatemeh Naqavi, 2021. "Built Environment Characteristics, Daily Travel, and Biometric Readings: Creation of an Experimental Tool Based on a Smartwatch Platform," Sustainability, MDPI, vol. 13(17), pages 1-21, September.
  21. Zhang, Weiwei & Li, Gaorong & Xue, Liugen, 2011. "Profile inference on partially linear varying-coefficient errors-in-variables models under restricted condition," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 3027-3040, November.
  22. Hans-Georg Müller & Chun-Lung Su & Stephen R. Dueker & Yumei Lin & Andrew Clifford & Bruce A. Buchholz & John S. Vogel, 2002. "Semiparametric Modeling of Labeled-Cell Kinetics, with Application to Isotope Labeling of Erythrocytes," Biometrics, The International Biometric Society, vol. 58(4), pages 937-945, December.
  23. Arnoud V. den Boer & Bert Zwart, 2014. "Simultaneously Learning and Optimizing Using Controlled Variance Pricing," Management Science, INFORMS, vol. 60(3), pages 770-783, March.
  24. den Boer, A.V., 2013. "Does adding data always improve linear regression estimates?," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 829-835.
  25. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
  26. Li, Gaorong & Lin, Lu & Zhu, Lixing, 2012. "Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 85-111.
  27. Ching-Kang Ing & Ching-Zong Wei, 2005. "A maximal moment inequality for long range dependent time series with applications to estimation and model selection," Econometrics 0508009, University Library of Munich, Germany.
  28. Bai, Z. D. & Guo, Meihui, 1999. "A paradox in least-squares estimation of linear regression models," Statistics & Probability Letters, Elsevier, vol. 42(2), pages 167-174, April.
  29. Velilla, Santiago, 2001. "On the bootstrap in misspecified regression models," Computational Statistics & Data Analysis, Elsevier, vol. 36(2), pages 227-242, April.
  30. Ciuperca, Gabriela, 2009. "The M-estimation in a multi-phase random nonlinear model," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 573-580, March.
  31. Jeongok Park & Chang Gi Park & Kyoungjin Lee, 2021. "A Quantile Regression Analysis of Factors Associated with First-Time Maternal Fatigue in Korea," IJERPH, MDPI, vol. 19(1), pages 1-12, December.
  32. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
  33. Chihwa Kao, 2001. "Asymptotic Inference in Censored Regression MOdels Revisited," Center for Policy Research Working Papers 36, Center for Policy Research, Maxwell School, Syracuse University.
  34. Dzhaparidze, K. & Spreij, P., 1989. "On SLLN for martingales with deterministic variation," Serie Research Memoranda 0079, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  35. Velilla Cerdan, Santiago, 1999. "Variable deletion conficence regions and bootstrapping in linear regression," DES - Working Papers. Statistics and Econometrics. WS 6351, Universidad Carlos III de Madrid. Departamento de Estadística.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.