TY - JOUR
T1 - A method for estimating the power of moments
AU - Chang, Shuhua
AU - Li, Deli
AU - Qi, Yongcheng
AU - Rosalsky, Andrew
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018
Y1 - 2018
N2 - Let X be an observable random variable with unknown distribution function F(x) = P(X≤ x) , − ∞ OpenSPiltSPi xOpenSPiltSPi ∞ , and let θ=sup{r≥0:E|X|rOpenSPiltSPi∞}.We call θ the power of moments of the random variable X. Let X1, X2, … , Xn be a random sample of size n drawn from F(⋅). In this paper we propose the following simple point estimator of θ and investigate its asymptotic properties: θˆn=lognlogmax1≤k≤n|Xk|where log x= ln (e∨ x) , − ∞ OpenSPiltSPi xOpenSPiltSPi ∞. In particular, we show that θˆn→Pθif and only iflimx→∞xrP(|X|CloseSPigtSPix)=∞∀rCloseSPigtSPiθ. This means that, under very reasonable conditions on F(⋅) , θˆ n is actually a consistent estimator of θ.
AB - Let X be an observable random variable with unknown distribution function F(x) = P(X≤ x) , − ∞ OpenSPiltSPi xOpenSPiltSPi ∞ , and let θ=sup{r≥0:E|X|rOpenSPiltSPi∞}.We call θ the power of moments of the random variable X. Let X1, X2, … , Xn be a random sample of size n drawn from F(⋅). In this paper we propose the following simple point estimator of θ and investigate its asymptotic properties: θˆn=lognlogmax1≤k≤n|Xk|where log x= ln (e∨ x) , − ∞ OpenSPiltSPi xOpenSPiltSPi ∞. In particular, we show that θˆn→Pθif and only iflimx→∞xrP(|X|CloseSPigtSPix)=∞∀rCloseSPigtSPiθ. This means that, under very reasonable conditions on F(⋅) , θˆ n is actually a consistent estimator of θ.
KW - Asymptotic theorems
KW - Consistent estimator
KW - Point estimator
KW - Power of moments
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U2 - 10.1186/s13660-018-1645-7
DO - 10.1186/s13660-018-1645-7
M3 - Article
C2 - 29540973
AN - SCOPUS:85043239130
SN - 1025-5834
VL - 2018
JO - Journal of Inequalities and Applications
JF - Journal of Inequalities and Applications
M1 - 54
ER -