• Title/Summary/Keyword: A-statistical convergence

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Asymptotic Theory for Multi-Dimensional Mode Estimator

  • Kim, Jean-Kyung
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.251-269
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    • 1994
  • In this paper we extend Kim and Pollard's cube root asymptotics to other rates of convergence, to establish an asymptotic theory for a multidimensional mode estimator based on uniform kernel with shrinking bandwidths. We obtain rates of convergence depending on shrinking rates of bandwidth and non-normal limit distributions. Optimal decreasing rates of bandwidth are discussed.

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Kernel Regression Estimation Under Dependence

  • Kim, Tae-Yoon;Kim, Donghoh
    • Journal of the Korean Statistical Society
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    • v.31 no.3
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    • pp.359-368
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    • 2002
  • Nonparametric kernel regression problem is considered for a stationary dependent sequence {(Xi, Yj) 1 j $\geq$ 1 }. In particular consistency and rates of convergence are discussed, which gives some useful insight for the effect of dependence for stationary $\alpha$-mixing sequences.

On triple sequence space of Bernstein-Stancu operator of rough Iλ-statistical convergence of weighted g (A)

  • Esi, A.;Subramanian, N.;Esi, Ayten
    • Annals of Fuzzy Mathematics and Informatics
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    • v.16 no.3
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    • pp.337-361
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    • 2018
  • We introduce and study some basic properties of rough $I_{\lambda}$-statistical convergent of weight g (A), where $g:{\mathbb{N}}^3{\rightarrow}[0,\;{\infty})$ is a function statisying $g(m,\;n,\;k){\rightarrow}{\infty}$ and $g(m,\;n,\;k){\not{\rightarrow}}0$ as $m,\;n,\;k{\rightarrow}{\infty}$ and A represent the RH-regular matrix and also prove the Korovkin approximation theorem by using the notion of weighted A-statistical convergence of weight g (A) limits of a triple sequence of Bernstein-Stancu polynomials.

WHEN CAN SUPPORT VECTOR MACHINE ACHIEVE FAST RATES OF CONVERGENCE?

  • Park, Chang-Yi
    • Journal of the Korean Statistical Society
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    • v.36 no.3
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    • pp.367-372
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    • 2007
  • Classification as a tool to extract information from data plays an important role in science and engineering. Among various classification methodologies, support vector machine has recently seen significant developments. The central problem this paper addresses is the accuracy of support vector machine. In particular, we are interested in the situations where fast rates of convergence to the Bayes risk can be achieved by support vector machine. Through learning examples, we illustrate that support vector machine may yield fast rates if the space spanned by an adopted kernel is sufficiently large.

Characterization of PEG-conjugated AuNPs by Using ToF-SIMS Imaging, Spectroscopic and Statistical Techniques

  • Shon, Hyun-Kyong;Son, Mi-Yong;Park, Hyun-Min;Moon, Dae-Won;Song, Nam-Woong;Lee, Tae-Geol
    • Proceedings of the Korean Vacuum Society Conference
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    • 2010.08a
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    • pp.73-73
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    • 2010
  • Various organic- and bio-conjugated nanoparticles have been studied extensively for biological applications in medical diagnoses and drug delivery systems. Gold nanoparticles (AuNP) and poly(ethylene glycol) (PEG) are known biocompatible materials to be used in vivo and are becoming increasingly important in biomedical applications. In this work, we investigated the stability of PEG-conjugated AuNPs, dialysis and centrifuge effects after synthesis or pegylation of AuNPs as a function of elapsed time by using ToF-SIMS imaging technique along with dynamic light scattering (DLS), UV-visible absorption spectroscopic and statistical analyses. Roughly 15-nm-sized AuNPs were synthesized in a citrate-conjugated form, and then converted into the thiol-terminated PEG (O-[2-(3-Mercaptopropionylamino)ethyl]-O'-methylpolyethyleneglycol, M.W.=5 kDa) form. Based on our data, we will show that ToF-SIMS imaging analysis along with DLS, UV-visible absorption and statistical analyses would be a useful method to evaluate stability of PEG-conjugated AuNPs in various environmental conditions.

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A Weak Convergence of the Linear Random Field Generated by Associated Randomvariables ℤ2

  • Kim, Tae-Sung;Ko, Mi-Hwa;Kim, Hyun-Chull
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.959-967
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    • 2008
  • In this paper we show the weak convergence of the linear random(multistochastic process) field generated by identically distributed 2-parameter array of associated random variables. Our result extends the result in Newman and Wright (1982) to the linear 2-parameter processes as well as the result in Kim and Ko (2003) to the 2-parameter case.

Weak Convergence of U-empirical Processes for Two Sample Case with Applications

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.31 no.1
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    • pp.109-120
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    • 2002
  • In this paper, we show the weak convergence of U-empirical processes for two sample problem. We use the result to show the asymptotic normality for the generalized dodges-Lehmann estimates with the Bahadur representation for quantifies of U-empirical distributions. Also we consider the asymptotic normality for the test statistics in a simple way.

A Note on the Asymptotic Property of S2 in Linear Regression Model with Correlated Errors

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.233-237
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    • 2003
  • An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

CONVERGENCE OF WEIGHTED U-EMPIRICAL PROCESSES

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.33 no.4
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    • pp.353-365
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    • 2004
  • In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

A Study on DDoS(Distributed Denial of Service) Attack Detection Model Based on Statistical (통계 기반 분산서비스거부(DDoS)공격 탐지 모델에 관한 연구)

  • Kook, Yoon-Ju;Kim, Yong-Ho;Kim, Jeom-Goo;Kim, Kiu-Nam
    • Convergence Security Journal
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    • v.9 no.2
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    • pp.41-48
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    • 2009
  • Distributed denial of service attack detection for more development and research is underway. The method of using statistical techniques, the normal packets and abnormal packets to identify efficient. In this paper several statistical techniques, using a mix of various offers a way to detect the attack. To verify the effectiveness of the proposed technique, it set packet filtering on router and the proposed DDoS attacks detection method on a Linux router. In result, the proposed technique was detect various attacks and provide normal service mostly.

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