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EXPONENTIAL PROBABILITY INEQUALITY FOR LINEARLY NEGATIVE QUADRANT DEPENDENT RANDOM VARIABLES

  • Ko, Mi-Hwa (Statistical Research Center For Complex Systems Seoul National University) ;
  • Choi, Yong-Kab (Division of Mathematics and Information Statistics Gyeongsang National University) ;
  • Choi, Yue-Soon (Division of Electric-Electronic-Information Engineering WonKwang University)
  • Published : 2007.01.31

Abstract

In this paper, a Berstein-Hoeffding type inequality is established for linearly negative quadrant dependent random variables. A condition is given for almost sure convergence and the associated rate of convergence is specified.

Keywords

References

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  3. Strong Laws of Large Numbers for Arrays of Rowwise NA and LNQD Random Variables vol.2011, 2011, https://doi.org/10.1155/2011/708087
  4. Complete convergence for weighted sums of LNQD random variables vol.87, pp.1, 2015, https://doi.org/10.1080/17442508.2014.931959
  5. Some mean convergence and complete convergence theorems for sequences of m-linearly negative quadrant dependent random variables vol.58, pp.5, 2013, https://doi.org/10.1007/s10492-013-0030-6
  6. Central limit theorem for stationary linear processes generated by linearly negative quadrant-dependent sequence vol.2012, pp.1, 2012, https://doi.org/10.1186/1029-242X-2012-45
  7. Some inequalities for a LNQD sequence with applications vol.2012, pp.1, 2012, https://doi.org/10.1186/1029-242X-2012-216
  8. Conditional limit theorems for conditionally linearly negative quadrant dependent random variables vol.166, pp.2, 2012, https://doi.org/10.1007/s00605-012-0373-1
  9. Limiting Behavior of the Maximum of the Partial Sum for Linearly Negative Quadrant Dependent Random Variables under Residual Cesàro Alpha-Integrability Assumption vol.2012, 2012, https://doi.org/10.1155/2012/735973
  10. Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence vol.2018, pp.1, 2018, https://doi.org/10.1186/s13660-017-1604-8
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