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Remarks on the strong law of large numbers for a triangular array of associated random variables

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Abstract

A strong law of large numbers for a triangular array of strictly stationary associated random variables is proved. It is used to derive the pointwise strong consistency of kernel type density estimator of the one-dimensional marginal density function of a strictly stationary sequence of associated random variables, and to obtain an improved version of a result by Van Ryzin (1969) on the strong consistency of density estimator for a sequence of independent and identically distributed random variables.

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References

  • Bagai I, Prakasa Rao BLS (1991) Estimation of the survival function for stationary associated processes. Statist Probab Letters 12:385–391

    Article  MATH  MathSciNet  Google Scholar 

  • Bagai I, Prakasa Rao BLS (1995) Kernel-type density and failure rate estimation for associated sequences. Ann Inst Statist Math 47:253–266

    Article  MATH  MathSciNet  Google Scholar 

  • Birkel T (1988a) Moment bounds for associated sequences. Ann Probab 16:1184–1193

    MATH  MathSciNet  Google Scholar 

  • Birkel T (1988b) On the convergence rate in the central limit theorem for associated processes. Ann Probab 16:1685–1698

    MATH  MathSciNet  Google Scholar 

  • Birkel T (1989) A note on the strong law of large numbers for positively dependent random variables. Statist Probab Letters 7:17–20

    Article  MathSciNet  Google Scholar 

  • Cox JT, Grimmett G (1984) Central limit theorems for associated random variables and the percolation model. Ann Probab 12:514–528

    MATH  MathSciNet  Google Scholar 

  • Esary J, Proschan F, Walkup D (1967) Association of random variables with applications. Ann Math Statist 38:1466–1474

    MathSciNet  Google Scholar 

  • Marshall AW, Olkin I (1967) A multivariate exponential distribution. J Amer Statist Assoc 62:30–44

    Article  MATH  MathSciNet  Google Scholar 

  • Newman CM (1980) Normal fluctuations and the FKG inequalities. Commn Math Phys 74:119–128

    Article  MATH  Google Scholar 

  • Newman CM (1984) Asymptotic independence and limit theorems for positively and negatively dependent random variables. In: Tong YL (Ed) Inequalities in Statistics and Probability. IMS, Hayward, CA 127–140

    Google Scholar 

  • Pitt L (1982) Positively correlated normal variables are associated. Ann Probab 10:496–499

    MATH  MathSciNet  Google Scholar 

  • Prakasa Rao BLS (1983) Nonparametric functional estimation. Academic Press, New York

    MATH  Google Scholar 

  • Prakasa Rao BLS (1993) Bernstein-type Inequality for Associated Sequences. In: Ghosh JK, Mitra SK, Parthasarathy KR, Prakasa Rao BLS (Eds) Statistics and Probability: A Raghu Raj Bahadur Festschrift. Wiley Eastern, New Delhi 499–509

    Google Scholar 

  • Roussas GG (1988) Nonparametric estimation in mixing sequences of random variables. J Statist Plann Inference 18:135–149

    Article  MATH  MathSciNet  Google Scholar 

  • Van Ryzin J (1969) On strong consistency of density estimates. Ann Math Statist 40:1765–1772

    MathSciNet  Google Scholar 

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Dewan, I., Rao, B.L.S.P. Remarks on the strong law of large numbers for a triangular array of associated random variables. Metrika 45, 225–234 (1997). https://doi.org/10.1007/BF02717105

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