Blockwise empirical likelihood for time series of counts
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References listed on IDEAS
- Francesco Bravo, 2009. "Blockwise generalized empirical likelihood inference for non-linear dynamic moment conditions models," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 208-231, July.
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- Daniel J. Nordman & Philipp Sibbertsen & Soumendra N. Lahiri, 2007.
"Empirical likelihood confidence intervals for the mean of a long-range dependent process,"
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Wiley Blackwell, vol. 28(4), pages 576-599, July.
- Nordman, Dan Nordman & Sibbertsen, Philipp & Lahiri, Soumendra N., 2005. "Empirical likelihood confidence intervals for the mean of a long-range dependent process," Hannover Economic Papers (HEP) dp-327, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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- Richard A. Davis & Rongning Wu, 2009. "A negative binomial model for time series of counts," Biometrika, Biometrika Trust, vol. 96(3), pages 735-749.
- Davidson, James, 1992. "A Central Limit Theorem for Globally Nonstationary Near-Epoch Dependent Functions of Mixing Processes," Econometric Theory, Cambridge University Press, vol. 8(03), pages 313-329, September.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Wu, Rongning, 2012. "On variance estimation in a negative binomial time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 145-155.
- repec:bla:scjsta:v:44:y:2017:i:4:p:843-865 is not listed on IDEAS
- Daniel J. Nordman & Helle Bunzel & Soumendra N. Lahiri, 2012.
"A Non-standard Empirical Likelihood for Time Series,"
CREATES Research Papers
2012-55, Department of Economics and Business Economics, Aarhus University.
- Nordman, Daniel J. & Bunzel, Helle & Lahiri, Soumendra N., 2013. "A Nonstandard Empirical Likelihood for Time Series," Staff General Research Papers Archive 37203, Iowa State University, Department of Economics.
More about this item
KeywordsAutocorrelation Generalized linear model Latent process Nonstationarity Overdispersion Regression analysis;
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