Asymptotic properties in partial linear models under dependence
Author
Abstract
Suggested Citation
DOI: 10.1007/BF02595701
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Mokkadem, Abdelkader, 1988. "Mixing properties of ARMA processes," Stochastic Processes and their Applications, Elsevier, vol. 29(2), pages 309-315, September.
- Schick, Anton, 1996. "Efficient estimation in a semiparametric additive regression model with autoregressive errors," Stochastic Processes and their Applications, Elsevier, vol. 61(2), pages 339-361, February.
- Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
- Rice, John, 1986. "Convergence rates for partially splined models," Statistics & Probability Letters, Elsevier, vol. 4(4), pages 203-208, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Xuejun Wang & Xin Deng & Shuhe Hu, 2018. "On consistency of the weighted least squares estimators in a semiparametric regression model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(7), pages 797-820, October.
- Dabo-Niang, Sophie & Guillas, Serge, 2010. "Functional semiparametric partially linear model with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 307-315, February.
- Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
- repec:wvu:wpaper:10-11 is not listed on IDEAS
- Zhou, Xing-cai & Lin, Jin-guan, 2013. "Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 251-270.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Linton, Oliver, 1995.
"Second Order Approximation in the Partially Linear Regression Model,"
Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
- Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.
- Wang Q. & Linton O. & Hardle W., 2004.
"Semiparametric Regression Analysis With Missing Response at Random,"
Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 334-345, January.
- Wolfgang Härdle & Oliver Linton & Wang, Qihua, 2003. "Semiparametric regression analysis with missing response at random," CeMMAP working papers CWP11/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Guang Cheng & Hao Zhang & Zuofeng Shang, 2015. "Sparse and efficient estimation for partial spline models with increasing dimension," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 93-127, February.
- Atak, Alev & Linton, Oliver & Xiao, Zhijie, 2011.
"A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom,"
Journal of Econometrics, Elsevier, vol. 164(1), pages 92-115, September.
- Alev Atak & Oliver Linton & Zhijie Xiao, 2010. "A Semiparametric Panel Model for unbalanced data with Application to Climate Change in the United Kingdom," Boston College Working Papers in Economics 762, Boston College Department of Economics.
- Alev Atak & Oliver Linton & Zhijie Xiao, 2011. "A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom," Post-Print hal-00844810, HAL.
- Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
- Zhu, Sha & Dekker, Rommert & van Jaarsveld, Willem & Renjie, Rex Wang & Koning, Alex J., 2017. "An improved method for forecasting spare parts demand using extreme value theory," European Journal of Operational Research, Elsevier, vol. 261(1), pages 169-181.
- Sung Wan Han & Rickson C. Mesquita & Theresa M. Busch & Mary E. Putt, 2014. "A method for choosing the smoothing parameter in a semi-parametric model for detecting change-points in blood flow," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 26-45, January.
- Wang, Xiaoguang & Lu, Dawei & Song, Lixin, 2013. "Statistical inference for partially linear stochastic models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 150-160.
- Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
- Roger D. Peng & Francesca Dominici & Thomas A. Louis, 2006. "Model choice in time series studies of air pollution and mortality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 179-203, March.
- Ibacache-Pulgar, Germán & Paula, Gilberto A., 2011. "Local influence for Student-t partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1462-1478, March.
- Gao, Jiti, 1994. "Asymptotic theory for partly linear models," MPRA Paper 40452, University Library of Munich, Germany, revised 02 Dec 1994.
- Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
- Golubev, Georgi & Härdle, Wolfgang, 1997. "On adaptive estimation in partial linear models," SFB 373 Discussion Papers 1997,100, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Yongsong Qin & Jianjun Li, 2011. "Empirical likelihood for partially linear models with missing responses at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 497-511.
- Wang, Qihua & Härdle, Wolfgang & Linton, Oliver, 2002.
"Semiparametric regression analysis under imputation for missing response data,"
SFB 373 Discussion Papers
2002,6, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Wolfgang Haerdle & Oliver Linton & Qihua Wang, 2003. "Semiparametric Regression Analysis under Imputation for Missing Response Data," STICERD - Econometrics Paper Series 454, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hardle, Wolfgang & Linton, Oliver & Wang, Qihua, 2003. "Semiparametric regression analysis under imputation for missing response data," LSE Research Online Documents on Economics 2206, London School of Economics and Political Science, LSE Library.
- Häggström, Jenny, 2013. "Bandwidth selection for backfitting estimation of semiparametric additive models: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 136-148.
- Ai, Chunrong & McFadden, Daniel, 1997. "Estimation of some partially specified nonlinear models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 1-37.
- repec:hal:journl:peer-00844810 is not listed on IDEAS
- Liang, Hua, 2006. "Estimation in partially linear models and numerical comparisons," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 675-687, February.
- Maria Durban & Christine A. Hackett & I. D. Currie, 1999. "Approximate Standard Errors in Semiparametric Models," Biometrics, The International Biometric Society, vol. 55(3), pages 699-703, September.
- Geert Bekaert & Robert J. Hodrick, 2001.
"Expectations Hypotheses Tests,"
Journal of Finance, American Finance Association, vol. 56(4), pages 1357-1394, August.
- Geert Bekaert & Robert J. Hodrick, 2000. "Expectations Hypotheses Tests," NBER Working Papers 7609, National Bureau of Economic Research, Inc.
More about this item
Keywords
Bandwidth selection; kernel smoothing; mixing; partial linear models; 62G05; 62G20; 62M10;All these keywords.
JEL classification:
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:10:y:2001:i:2:p:333-355. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.