Mynbaev, Kairat (2011): Distributions escaping to infinity and the limiting power of the Cliff-Ord test for autocorrelation. Published in: ISRN Probability and Statistics , Vol. 2012, No. Article ID 926164 (24 October 2012): pp. 1-39.
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Abstract
We 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.
Item Type: | MPRA Paper |
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Original Title: | Distributions escaping to infinity and the limiting power of the Cliff-Ord test for autocorrelation |
Language: | English |
Keywords: | improper random variable, Cliff-Ord test, autocorrelation, spatial correlation, characteristic function, almost periodic functions |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models |
Item ID: | 44402 |
Depositing User: | Kairat Mynbaev |
Date Deposited: | 15 Feb 2013 17:06 |
Last Modified: | 01 Oct 2019 18:02 |
References: | K. Yosida, Functional Analysis, Springer, 1965. E. Lukacs, Characteristic Functions, Griffn, 2nd edition, 1970. N. I. Akhiezer and I.M. Glazman, Theory of Linear Operators in Hilbert Space, Dover Publications, 1993. F. Martellosio, “Power properties of invariant tests for spatial autocorrelation in linear regression,” Econometric Theory, vol. 26, no. 1, pp. 152–186, 2010. A. D. Cliff and J. K. Ord, Spatial Processes: Models & Applications, Pion, 1981. W. Kr¨amer, “Finite sample power of Cliff-Ord-type tests for spatial disturbance correlation in linear regression,” Journal of Statistical Planning and Inference, vol. 128, no. 2, pp. 489–496, 2005. F. Martellosio, “Testing for spatial autocorrelation: the regressors that make the power disappear,” Econometric Reviews, vol. 31, no. 2, pp. 215–240, 2012. T. Kariya, “Locally robust tests for serial correlation in least squares regression,” The Annals of Statistics, vol. 8, no. 5, pp. 1065–1070, 1980. R. M. Dudley, Uniform Central Limit Theorems, vol. 63, Cambridge University Press, 1999. P. Billingsley, Convergence of Probability Measures, John Wiley & Sons, 1968. A. N. Kolmogorov and S. V. Fomin, Introduction to the Theory of Functions and Functional Analysis, Nauka, 1972. V. I. Burenkov, “Approximation by infinitely differentiable functions with preservation of boundary values ,” in Proceedings of the Steklov Mathematical Institute, vol. 180, pp. 76–79, 1989. C. R. Rao, Linear Statistical Inference and Its Applications, John Wiley & Sons, 1965. N. Dunford and J. T. Schwartz, Linear Operators. Part I: General Theory, Wiley-Interscience, 1958. B. Van Es and H.-W. Uh, “Asymptotic normality of kernel-type deconvolution estimators,” Scandinavian Journal of Statistics, vol. 32, no. 3, pp. 467–483, 2005. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/44402 |