• Title/Summary/Keyword: mean convergence theorem

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WEAK CONVERGENCE FOR STATIONARY BOOTSTRAP EMPIRICAL PROCESSES OF ASSOCIATED SEQUENCES

  • Hwang, Eunju
    • Journal of the Korean Mathematical Society
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    • v.58 no.1
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    • pp.237-264
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    • 2021
  • In this work the stationary bootstrap of Politis and Romano [27] is applied to the empirical distribution function of stationary and associated random variables. A weak convergence theorem for the stationary bootstrap empirical processes of associated sequences is established with its limiting to a Gaussian process almost surely, conditionally on the stationary observations. The weak convergence result is proved by means of a random central limit theorem on geometrically distributed random block size of the stationary bootstrap procedure. As its statistical applications, stationary bootstrap quantiles and stationary bootstrap mean residual life process are discussed. Our results extend the existing ones of Peligrad [25] who dealt with the weak convergence of non-random blockwise empirical processes of associated sequences as well as of Shao and Yu [35] who obtained the weak convergence of the mean residual life process in reliability theory as an application of the association.

A NEW BIHARMONIC KERNEL FOR THE UPPER HALF PLANE

  • Abkar, Ali
    • Journal of the Korean Mathematical Society
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    • v.43 no.6
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    • pp.1169-1181
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    • 2006
  • We introduce a new biharmonic kernel for the upper half plane, and then study the properties of its relevant potentials, such as the convergence in the mean and the boundary behavior. Among other things, we shall see that Fatou's theorem is valid for these potentials, so that the biharmonic Poisson kernel resembles the usual Poisson kernel for the upper half plane.

CONVERGENCE OF WEIGHTED SUMS FOR DEPENDENT RANDOM VARIABLES

  • Liang, Han-Yang;Zhang, Dong-Xia;Baek, Jong-Il
    • Journal of the Korean Mathematical Society
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    • v.41 no.5
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    • pp.883-894
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    • 2004
  • We discuss in this paper the strong convergence for weighted sums of negative associated (in abbreviation: NA) arrays. Meanwhile, the central limit theorem for weighted sums of NA variables and linear process based on NA variables is also considered. As corollary, we get the results on iid of Li et al. ([10]) in NA setting.

MEAN CONVERGENCE THEOREMS AND WEAK LAWS OF LARGE NUMBERS FOR DOUBLE ARRAYS OF RANDOM ELEMENTS IN BANACH SPACES

  • Dung, Le Van;Tien, Nguyen Duy
    • Bulletin of the Korean Mathematical Society
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    • v.47 no.3
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    • pp.467-482
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    • 2010
  • For a double array of random elements {$V_{mn};m{\geq}1,\;n{\geq}1$} in a real separable Banach space, some mean convergence theorems and weak laws of large numbers are established. For the mean convergence results, conditions are provided under which $k_{mn}^{-\frac{1}{r}}\sum{{u_m}\atop{i=1}}\sum{{u_n}\atop{i=1}}(V_{ij}-E(V_{ij}|F_{ij})){\rightarrow}0$ in $L_r$ (0 < r < 2). The weak law results provide conditions for $k_{mn}^{-\frac{1}{r}}\sum{{T_m}\atop{i=1}}\sum{{\tau}_n\atop{j=1}}(V_{ij}-E(V_{ij}|F_{ij})){\rightarrow}0$ in probability where {$T_m;m\;{\geq}1$} and {${\tau}_n;n\;{\geq}1$} are sequences of positive integer-valued random variables, {$k_{mn};m{{\geq}}1,\;n{\geq}1$} is an array of positive integers. The sharpness of the results is illustrated by examples.

On Convergence in p-Mean of Randomly Indexed Partial Sums and Some First Passage Times for Random Variables Which Are Dependent or Non-identically Distributed

  • Hong, Dug-Hun
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.175-183
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    • 1996
  • Let $S_n,n$ = 1, 2,... denote the partial sums of not necessarily in-dependent random variables. Let N(c) = min${ n ; S_n > c}$, c $\geq$ 0. Theorem 2 states that N (c), (suitably normalized), tends to 0 in p-mean, 1 $\leq$ p < 2, as c longrightarrow $\infty$ under mild conditions, which generalizes earlier result by Gut(1974). The proof follows by applying Theorem 1, which generalizes the known result $E$\mid$S_n$\mid$^p$ = o(n), 0 < p< 2, as n .rarw..inf. to randomly indexed partial sums.

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Bicubic Splines in Problems of Modeling of Multidimensional Signals

  • Bahramov, Sayfiddin;Jovliev, Sanjar
    • Journal of information and communication convergence engineering
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    • v.9 no.4
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    • pp.420-423
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    • 2011
  • The paper is devoted to problem of spline modeling of multidimensional signals. A new method of nodes location for curves and surfaces computer construction in multidimensional spaces by means of B-splines is presented. The criteria are which links a square-mean error caused by high frequency spline distortions and approximation intervals is determined and necessary theorem is proved. In this method use a theory of entire multidimensional spectra and may be extended for the spaces of three, four and more variables.

An Equilibrium Analysis of the Constrained Mean-Price Sealed Bid Auction (제한적 평균가낙찰제 경매방식의 균형분석)

  • Seo, Yong-Mo;Rhee, Byungchae
    • Journal of the Korea Convergence Society
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    • v.10 no.1
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    • pp.205-214
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    • 2019
  • In Korea, the first-price sealed bid auction and the constrained mean-price sealed bid auction(buchal-je in Korean) have been used alternatively as procurement auctions. In this paper, we characterize the constrained mean-price sealed bid auction in the context of mechanism design. We consider the general ?-bidder case in which each bidder has private information. Under the assumptions of uniformly distributed valuations and linear strategies, we derive the equilibrium of the constrained mean-price sealed bid auction. Furthermore, we analyze the efficiency and the expected revenue of this auction mechanism in comparison with the first-price sealed bid auction. Finally, we conclude with the critical remarks on the practical intention of the government which uses this auction.

On the Bayes risk of a sequential design for estimating a mean difference

  • Sangbeak Ye;Kamel Rekab
    • Communications for Statistical Applications and Methods
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    • v.31 no.4
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    • pp.427-440
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    • 2024
  • The problem addressed is that of sequentially estimating the difference between the means of two populations with respect to the squared error loss, where each population distribution is a member of the one-parameter exponential family. A Bayesian approach is adopted in which the population means are estimated by the posterior means at each stage of the sampling process and the prior distributions are not specified but have twice continuously differentiable density functions. The main result determines an asymptotic second-order lower bound, as t → ∞, for the Bayes risk of a sequential procedure that takes M observations from the first population and t - M from the second population, where M is determined according to a sequential design, and t denotes the total number of observations sampled from both populations.