A New Mixing Condition
Author
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
- Beare, Brendan K., 2009. "A generalization of Hoeffding's lemma, and a new class of covariance inequalities," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 637-642, March.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Brendan K. Beare, 2010.
"Copulas and Temporal Dependence,"
Econometrica, Econometric Society, vol. 78(1), pages 395-410, January.
- Beare, Brendan, 2008. "Copulas and Temporal Dependence," University of California at San Diego, Economics Working Paper Series qt2880q2jq, Department of Economics, UC San Diego.
- Beare, Brendan K., 2009. "Copulas and Temporal Dependence," University of California at San Diego, Economics Working Paper Series qt87p829d4, Department of Economics, UC San Diego.
- Beare, Brendan K., 2009. "A generalization of Hoeffding's lemma, and a new class of covariance inequalities," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 637-642, March.
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.- Jerôme Dedecker & Paul Doukhan, 2002. "A New Covariance Inequality and Applications," Working Papers 2002-25, Center for Research in Economics and Statistics.
- Hwang, Eunju & Shin, Dong Wan, 2014. "Infinite-order, long-memory heterogeneous autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 339-358.
- Guessoum, Zohra & Ould Saïd, Elias & Sadki, Ourida & Tatachak, Abdelkader, 2012. "A note on the Lynden-Bell estimator under association," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1994-2000.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Paul Doukhan & Gabriel Lang & Anne Leucht & Michael H. Neumann, 2015.
"Recent developments in bootstrap methods for dependent data,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 290-314, May.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
- Carvalho, Carlos & Masini, Ricardo & Medeiros, Marcelo C., 2018.
"ArCo: An artificial counterfactual approach for high-dimensional panel time-series data,"
Journal of Econometrics, Elsevier, vol. 207(2), pages 352-380.
- Carlos Viana de Carvalho & Ricardo Masini & Marcelo Cunha Medeiros, 2016. "ARCO: an artificial counterfactual approach for high-dimensional panel time-series data," Textos para discussão 653, Department of Economics PUC-Rio (Brazil).
- Carvalho, Carlos Viana de & Masini, Ricardo Pereira & Medeiros, Marcelo C., 2017. "Arco: an artificial counterfactual approach for high-dimensional panel time-series data," Textos para discussão 454, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
- Hwang, Eunju & Shin, Dong Wan, 2012. "Strong consistency of the stationary bootstrap under ψ-weak dependence," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 488-495.
- Garg, Mansi & Dewan, Isha, 2015. "On asymptotic behavior of U-statistics for associated random variables," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 209-220.
- Eunju Hwang & Dong Shin, 2016. "Kernel estimators of mode under $$\psi $$ ψ -weak dependence," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 301-327, April.
- Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021.
"Limit theorems for network dependent random variables,"
Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
- Denis Kojevnikov & Vadim Marmer & Kyungchul Song, 2019. "Limit Theorems for Network Dependent Random Variables," Papers 1903.01059, arXiv.org, revised Feb 2021.
- Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
- Alain Durmus & Eric Moulines & Alexey Naumov & Sergey Samsonov, 2024. "Probability and Moment Inequalities for Additive Functionals of Geometrically Ergodic Markov Chains," Journal of Theoretical Probability, Springer, vol. 37(3), pages 2184-2233, September.
- Dedecker, Jérôme & Prieur, Clémentine, 2007. "An empirical central limit theorem for dependent sequences," Stochastic Processes and their Applications, Elsevier, vol. 117(1), pages 121-142, January.
- McElroy, Tucker & Politis, Dimitris N., 2013.
"Distribution theory for the studentized mean for long, short, and negative memory time series,"
Journal of Econometrics, Elsevier, vol. 177(1), pages 60-74.
- McElroy, Tucker S & Politis, D N, 2011. "Distribution Theory for the Studentized Mean for Long, Short, and Negative Memory Time Series," University of California at San Diego, Economics Working Paper Series qt0dr145dt, Department of Economics, UC San Diego.
- McElroy, Tucker S. & Politis, Dimitris N., 2012. "Distribution Theory for the Studentized Mean for Long, Short, and Negative Memory Time Series," University of California at San Diego, Economics Working Paper Series qt35c7r55c, Department of Economics, UC San Diego.
- 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.
- Sancetta, Alessio, 2008.
"Sample covariance shrinkage for high dimensional dependent data,"
Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 949-967, May.
- Sancetta, A., 2006. "Sample Covariance Shrinkage for High Dimensional Dependent Data," Cambridge Working Papers in Economics 0637, Faculty of Economics, University of Cambridge.
- Pinkse, Joris & Shen, Lihong & Slade, Margaret, 2007. "A central limit theorem for endogenous locations and complex spatial interactions," Journal of Econometrics, Elsevier, vol. 140(1), pages 215-225, September.
- Mamadou Lamine Diop & William Kengne, 2023. "A general procedure for change-point detection in multivariate time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 1-33, March.
- Xuan Liang & Jiti Gao & Xiaodong Gong, 2022.
"Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1784-1802, October.
- Xuan Liang & Jiti Gao & Xiaodong Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Monash Econometrics and Business Statistics Working Papers 5/21, Monash University, Department of Econometrics and Business Statistics.
- Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
- Christis Katsouris, 2022. "Asymptotic Theory for Unit Root Moderate Deviations in Quantile Autoregressions and Predictive Regressions," Papers 2204.02073, arXiv.org, revised Aug 2023.
- Cui, Yunwei & Zheng, Qi, 2017. "Conditional maximum likelihood estimation for a class of observation-driven time series models for count data," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 193-201.
More about this item
Keywords
Mixing; Weak Dependence; Hardy-Krause Variation;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2007-09-09 (Econometrics)
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:oxf:wpaper:348. 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: Anne Pouliquen (email available below). General contact details of provider: https://edirc.repec.org/data/sfeixuk.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.