Distributions escaping to infinity and the limiting power of the Cliff-Ord test for autocorrelation
AbstractWe consider a family of proper random variables which converges to an improper random variable. The limit in distribution is found and applied to obtain a closed-form expression for the limiting power of the Cliff-Ord test for autocorrelation. The applications include the theory of characteristic functions of proper random variables, the theory of almost periodic functions, and the test for spatial correlation in a linear regression model.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 44402.
Date of creation: 01 Jan 2011
Date of revision: 18 Sep 2012
Publication status: Published in ISRN Probability and Statistics Article ID 926164.2012(2012): pp. 1-39
improper random variable; Cliff-Ord test; autocorrelation; spatial correlation; characteristic function; almost periodic functions;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
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- Bert Van Es & Hae-Won Uh, 2005. "Asymptotic Normality of Kernel-Type Deconvolution Estimators," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(3), pages 467-483.
- Martellosio, Federico, 2008. "Testing for spatial autocorrelation: the regressors that make the power disappear," MPRA Paper 10542, University Library of Munich, Germany.
- Martellosio, Federico, 2010. "Power Properties Of Invariant Tests For Spatial Autocorrelation In Linear Regression," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 26(01), pages 152-186, February.
- Preinerstorfer, David & Pötscher, Benedikt M., 2014. "On the Power of Invariant Tests for Hypotheses on a Covariance Matrix," MPRA Paper 55059, University Library of Munich, Germany.
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