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Strong laws for weighted sums of i.i.d. random variables

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Abstract

Strong laws are established for linear statistics thatare weighted sums of a random sample. We show extensions of theMarcinkiewicz-Zygmund strong laws under certain moment condi-tions on both the weights and the distribution. The result obtainedextends and sharpens the result of Sung ([12]).

참고문헌 (11)

  1. "Marcinkiewicz strong laws", pp.105~112 (2000)
  2. "Almost sure convergence theorems of weighted sums of random variables", pp.365~377 (1987)
  3. "it Probability Theory: Independence Interchangeability, Martingales" (1997)
  4. "A strong law for weighted sums of i.i.d. random variables", pp.625~641 (1995)
  5. "On a theorem ofHsu-Robbins", pp.286~ (1949)
  6. "\it Negativeassociated of random variables with application}", pp.286~ (1983)
  7. "Limittheorems of probability theory sequences of independent randomvariables" (1995)
  8. "A comparison theorem on moment inequalitiesbetween Negatively associated and independent random variables", pp.343~356 (2000)
  9. "Strong laws for weighted sums ofi.i.d. random variables", pp.413~419 (2001)
  10. "Strong laws forweighted sums of i.i.d. random variables", 4, pp.607~615 (2002)
  11. "Onthe strong convergence of a weighted sums Statist", pp.19~22 (1999)

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