Estimation of latent factors for high-dimensional time series
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014.
"Forecasting with factor-augmented error correction models,"
International Journal of Forecasting,
Elsevier, vol. 30(3), pages 589-612.
- Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2009. "Forecasting with Factor-Augmented Error Correction Models," Discussion Papers 09-06, Department of Economics, University of Birmingham.
- Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2010. "Forecasting with Factor-augmented Error Correction Models," CEPR Discussion Papers 7677, C.E.P.R. Discussion Papers.
- Igor Masten & Massimiliano Marcellino & Anindya Banerjeey, 2009. "Forecasting with Factor-augmented Error Correction Models," RSCAS Working Papers 2009/32, European University Institute.
- Chang, Jinyuan & Guo, Bin & Yao, Qiwei, 2015. "High dimensional stochastic regression with latent factors, endogeneity and nonlinearity," LSE Research Online Documents on Economics 61886, London School of Economics and Political Science, LSE Library.
- Chen, Songxi, 2012. "Two Sample Tests for High Dimensional Covariance Matrices," MPRA Paper 46026, University Library of Munich, Germany.
- He, Jing & Chen, Song Xi, 2016. "Testing super-diagonal structure in high dimensional covariance matrices," Journal of Econometrics, Elsevier, vol. 194(2), pages 283-297.
- Li, Weiming & Gao, Jing & Li, Kunpeng & Yao, Qiwei, 2016. "Modelling multivariate volatilities via latent common factors," LSE Research Online Documents on Economics 68121, London School of Economics and Political Science, LSE Library.
- repec:bla:jtsera:v:38:y:2017:i:2:p:285-307 is not listed on IDEAS
- Jianqing Fan & Yuan Liao & Martina Mincheva, 2013.
"Large covariance estimation by thresholding principal orthogonal complements,"
Journal of the Royal Statistical Society Series B,
Royal Statistical Society, vol. 75(4), pages 603-680, September.
- Fan, Jianqing & Liao, Yuan & Mincheva, Martina, 2011. "Large covariance estimation by thresholding principal orthogonal complements," MPRA Paper 38697, University Library of Munich, Germany.
- Poncela, Pilar & Guerrero, Víctor & Islas C., Alejandro & Rodríguez, Julio & Sánchez-Mangas, Rocío, 2014. "Mexico: Combining monthly inflation predictions from surveys," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
- Matteo Barigozzi & Lorenzo Trapani, 2017. "Sequential testing for structural stability in approximate factor models," Papers 1708.02786, arXiv.org, revised Mar 2018.
- Passemier, Damien & Yao, Jianfeng, 2014. "Estimation of the number of spikes, possibly equal, in the high-dimensional case," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 173-183.
- Liu, Xialu & Xiao, Han & Chen, Rong, 2016. "Convolutional autoregressive models for functional time series," Journal of Econometrics, Elsevier, vol. 194(2), pages 263-282.
- Chang, Jinyuan & Guo, Bin & Yao, Qiwei, 2015. "High dimensional stochastic regression with latent factors, endogeneity and nonlinearity," Journal of Econometrics, Elsevier, vol. 189(2), pages 297-312.
More about this item
StatisticsAccess and download statistics
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:oup:biomet:v:98:y:2011:i:4:p:901-918. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum). General contact details of provider: https://academic.oup.com/biomet .
We have no references for this item. You can help adding them by using this form .