Consistency results for the kernel density estimate on continuous time stationary and dependent data
Author
Abstract
Suggested Citation
DOI: 10.1016/j.spl.2013.01.024
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
- Wu, Wei Biao & Huang, Yinxiao & Huang, Yibi, 2010. "Kernel estimation for time series: An asymptotic theory," Stochastic Processes and their Applications, Elsevier, vol. 120(12), pages 2412-2431, December.
- Castellana, J. V. & Leadbetter, M. R., 1986. "On smoothed probability density estimation for stationary processes," Stochastic Processes and their Applications, Elsevier, vol. 21(2), pages 179-193, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- El Heda, Khadijetou & Louani, Djamal, 2018. "Optimal bandwidth selection in kernel density estimation for continuous time dependent processes," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 9-19.
- Laïb, Naâmane & Louani, Djamal, 2019. "Asymptotic normality of kernel density function estimator from continuous time stationary and dependent processes," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 187-196.
- Chaouch, Mohamed & Laïb, Naâmane, 2019. "Optimal asymptotic MSE of kernel regression estimate for continuous time processes with missing at random response," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
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.- Dalalyan Arnak S. & Kutoyants Yury A., 2004. "On second order minimax estimation of invariant density for ergodic diffusion," Statistics & Risk Modeling, De Gruyter, vol. 22(1), pages 17-42, January.
- Labrador, Boris, 2008. "Strong pointwise consistency of the kT -occupation time density estimator," Statistics & Probability Letters, Elsevier, vol. 78(9), pages 1128-1137, July.
- Toshio Honda, 2013.
"Nonparametric quantile regression with heavy-tailed and strongly dependent errors,"
Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 23-47, February.
- Toshio Honda, 2010. "Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors," Global COE Hi-Stat Discussion Paper Series gd10-157, Institute of Economic Research, Hitotsubashi University.
- Wu, Wei Biao & Huang, Yinxiao & Huang, Yibi, 2010. "Kernel estimation for time series: An asymptotic theory," Stochastic Processes and their Applications, Elsevier, vol. 120(12), pages 2412-2431, December.
- Gourieroux, Christian & Jasiak, Joann, 2019.
"Robust analysis of the martingale hypothesis,"
Econometrics and Statistics, Elsevier, vol. 9(C), pages 17-41.
- Christian Gouriéroux & Joann Jasiak, 2016. "Robust Analysis of the Martingale Hypothesis," Working Papers 2016-18, Center for Research in Economics and Statistics.
- Oberhofer, Walter & Haupt, Harry, 2005. "The asymptotic distribution of the unconditional quantile estimator under dependence," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 243-250, July.
- Robinson, Peter M. & Thawornkaiwong, Supachoke, 2012. "Statistical inference on regression with spatial dependence," Journal of Econometrics, Elsevier, vol. 167(2), pages 521-542.
- Longla, Martial & Peligrad, Magda & Sang, Hailin, 2015. "On kernel estimators of density for reversible Markov chains," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 149-157.
- Guillou, Armelle & Merlevède, Florence, 2001. "Estimation of the Asymptotic Variance of Kernel Density Estimators for Continuous Time Processes," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 114-137, October.
- Natalia Markovich & Jorma Kilpi, 2009. "Bivariate statistical analysis of TCP-flow sizes and durations," Annals of Operations Research, Springer, vol. 170(1), pages 199-216, September.
- Negri, Ilia, 2001. "On efficient estimation of invariant density for ergodic diffusion processes," Statistics & Probability Letters, Elsevier, vol. 51(1), pages 79-85, January.
- Mielniczuk, Jan, 1997. "On the asymptotic mean integrated squared error of a kernel density estimator for dependent data," Statistics & Probability Letters, Elsevier, vol. 34(1), pages 53-58, May.
- Blanke, D. & Bosq, D., 1997. "Accurate rates of density estimators for continuous-time processes," Statistics & Probability Letters, Elsevier, vol. 33(2), pages 185-191, April.
- Wang, Yizao & Woodroofe, Michael, 2014. "On the asymptotic normality of kernel density estimators for causal linear random fields," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 201-213.
- Salim Bouzebda & Mohamed Chaouch & Sultana Didi Biha, 2022. "Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 737-771, August.
- Kutoyants, Yu. A., 1997. "Some problems of nonparametric estimation by observations of ergodic diffusion process," Statistics & Probability Letters, Elsevier, vol. 32(3), pages 311-320, March.
- Koul, Hira L. & Zhu, Xiaoqing, 2015. "Goodness-of-fit testing of error distribution in nonparametric ARCH(1) models," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 141-160.
- Sköld, Martin & Hössjer, Ola, 1999. "On the asymptotic variance of the continuous-time kernel density estimator," Statistics & Probability Letters, Elsevier, vol. 44(1), pages 97-106, August.
- Timothy Fortune & Hailin Sang, 2020. "Shannon Entropy Estimation for Linear Processes," JRFM, MDPI, vol. 13(9), pages 1-13, September.
- Tomas Ruzgas & Mantas Lukauskas & Gedmantas Čepkauskas, 2021. "Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model," Mathematics, MDPI, vol. 9(21), pages 1-22, October.
More about this item
Keywords
Consistency; Continuous time; Density function; Kernel estimator; Rate of convergence;All these keywords.
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:eee:stapro:v:83:y:2013:i:4:p:1262-1270. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.