• Title/Summary/Keyword: rate of statistical convergence

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On the Plug-in Bandwidth Selectors in Kernel Density Estimation

  • Park, Byeong-Uk
    • Journal of the Korean Statistical Society
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    • v.18 no.2
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    • pp.107-117
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    • 1989
  • A stronger result than that of Park and Marron (1994) is proved here on the asymptotic distribution of the plug-in bandwidth selector. The new result is that the plug-in bandwidth selector may have the rate of convergence ($n^{-4/13}$ with less smoothness conditions on the unknown density functions than as described in Park and Marron's paper. Together with this, a class of various plug-in bandwidth selectors are considered and their asymptotic distributions are given. Finally, some ideas of possible improvements on those plug-in bandwidth selectors are provided.

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Asymptotics of the Variance Ratio Test for MA Unit Root Processes

  • Lee, Jin
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.223-229
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    • 2010
  • We consider the asymptotic results of the variance ratio statistic when the underlying processes have moving average(MA) unit roots. This degenerate situation of zero spectral density near the origin cause the limit of the variance ratio to become zero. Its asymptotic behaviors are different from non-degenerating case, where the convergence rate of the variance ratio statistic is formally derived.

A Berry-Esseen Type Bound in Kernel Density Estimation for a Random Left-Truncation Model

  • Asghari, P.;Fakoor, V.;Sarmad, M.
    • Communications for Statistical Applications and Methods
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    • v.21 no.2
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    • pp.115-124
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    • 2014
  • In this paper we derive a Berry-Esseen type bound for the kernel density estimator of a random left truncated model, in which each datum (Y) is randomly left truncated and is sampled if $Y{\geq}T$, where T is the truncation random variable with an unknown distribution. This unknown distribution is estimated with the Lynden-Bell estimator. In particular the normal approximation rate, by choice of the bandwidth, is shown to be close to $n^{-1/6}$ modulo logarithmic term. We have also investigated this normal approximation rate via a simulation study.

비모수적 회귀함수 추정에서 평활량의 선택에 관한 연구

  • 석경하
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.39-49
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    • 1996
  • 비모수적 커널 회귀함수 추정법에서 평활량(bandwidth of smoothing parameter)의 선택은 아주 중요한 문제이다. 교차타당성(cross-validation) 방법에 의한 평활량은 최적평활량으로의 상대적 수렴속도(relative convergence rate)가 $n^{-1/10}$로 상당히 느리다는 것을 알고 있다. 본 연구는 삽입방법(plug-in method)에 의해 선택된 평활량의 상대적 수렴속도가 교차타당성 방법보다 더 빠른 $n^{-2/7}$이 됨을 보였다. 그리고 모의실험을 통하여 소 표본에서도 삽입방법이 교차타당성 방법보다 우수함을 입증하였다.

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EMPIRICAL BAYES ESTIMATION OF RESIDUAL SURVIVAL FUNCTION AT AGE

  • Liang, Ta-Chen
    • Journal of the Korean Statistical Society
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    • v.33 no.2
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    • pp.191-202
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    • 2004
  • The paper considers nonparametric empirical Bayes estimation of residual survival function at age t using a Dirichlet process prior V(a). Empirical Bayes estimators are proposed for the case where both the function ${\alpha}$(0, $\chi$] and the size a(R$\^$+/) are unknown. It is shown that the proposed empirical Bayes estimators are asymptotically optimal at a rate n$\^$-1/, where n is the number of past data available for the present estimation problem. Therefore, the result of Lahiri and Park (1988) in which a(R$\^$+/) is assumed to be known and a rate n$\^$-1/ is achieved, is extended to a(R$\^$+/) unknown case.

Enhanced Block-Based Adaptive Loop Filter with Multiple Symmetric Structures for Video Coding

  • Lee, Ha-Hyun;Lim, Sung-Chang;Choi, Hae-Chul;Jeong, Se-Yoon;Kim, Jong-Ho;Choi, Jin-Soo
    • ETRI Journal
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    • v.32 no.4
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    • pp.626-629
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    • 2010
  • In this letter, we present an enhanced block-based adaptive loop filter (E-BALF) with multiple filter symmetric structures. The E-BALF adapts various filter symmetric structures in a rate-distortion optimization sense, reflecting the statistical properties of each image in a video sequence. Experimental results show that the proposed method achieves a reduction in the Bj${\phi}$ntegaard delta (BD)-bitrate by an average of 9.60% compared with Joint Model 11.0 of H.264/AVC. Compared to the state-of-the-art BALF, a reduction of up to 1.13% in BD-bitrate is achieved.

Wavelet Estimation of Regression Functions with Errors in Variables

  • Kim, Woo-Chul;Koo, Ja-Yong
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.849-860
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    • 1999
  • This paper addresses the issue of estimating regression function with errors in variables using wavelets. We adopt a nonparametric approach in assuming that the regression function has no specific parametric form, To account for errors in covariates deconvolution is involved in the construction of a new class of linear wavelet estimators. using the wavelet characterization of Besov spaces the question of regression estimation with Besov constraint can be reduced to a problem in a space of sequences. Rates of convergence are studied over Besov function classes $B_{spq}$ using $L_2$ error measure. It is shown that the rates of convergence depend on the smoothness s of the regression function and the decay rate of characteristic function of the contaminating error.

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Precise Rates in Complete Moment Convergence for Negatively Associated Sequences

  • Ryu, Dae-Hee
    • Communications for Statistical Applications and Methods
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    • v.16 no.5
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    • pp.841-849
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    • 2009
  • Let {$X_n$, n ${\ge}$ 1} be a negatively associated sequence of identically distributed random variables with mean zeros and positive finite variances. Set $S_n$ = ${\Sigma}^n_{i=1}\;X_i$. Suppose that 0 < ${\sigma}^2=EX^2_1+2{\Sigma}^{\infty}_{i=2}\;Cov(X_1,\;X_i)$ < ${\infty}$. We prove that, if $EX^2_1(log^+{\mid}X_1{\mid})^{\delta}$ < ${\infty}$ for any 0< ${\delta}{\le}1$, then $\lim_{{\epsilon}\downarrow0}{\epsilon}^{2{\delta}}\sum_{{n=2}}^{\infty}\frac{(logn)^{\delta-1}}{n^2}ES^2_nI({\mid}S_n{\mid}\geq{\epsilon}{\sigma}\sqrt{nlogn}=\frac{E{\mid}N{\mid}^{2\delta+2}}{\delta}$, where N is the standard normal random variable. We also prove that if $S_n$ is replaced by $M_n=max_{1{\le}k{\le}n}{\mid}S_k{\mid}$ then the precise rate still holds. Some results in Fu and Zhang (2007) are improved to the complete moment case.

Proposed One-Minute Rain Rate Conversion Method for Microwave Applications in Korea

  • Shrestha, Sujan;Choi, Dong-You
    • Journal of information and communication convergence engineering
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    • v.14 no.3
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    • pp.153-162
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    • 2016
  • Microwave and millimeter waves are considered suitable frequency ranges for diverse applications. The prediction of rain attenuation required the 1-min rainfall rate distribution, particularly for data obtained locally from experimental measurement campaigns over a given location. Rainfall rate data acquired from Korea Meteorological Administration (KMA) for nine major sites are analyzed to investigate the statistical stability of the cumulative distribution of rainfall rate, as obtained from a 10-year measurement. In this study, we use the following rain rate conversion techniques: Segal, Burgueno et al., Chebil and Rahman, exponential, and proposed global coefficient methods. The performance of the proposed technique is tested against that of the existing rain rate conversion techniques. The nine sites considered for the average 1-min rain rate derivation are Gwangju, Daegu, Daejeon, Busan, Seogwipo, Seoul, Ulsan, Incheon, and Chuncheon. In this paper, we propose a conversion technique for a suitable estimation of the 1-min rainfall rate distribution.

Application of machine learning for merging multiple satellite precipitation products

  • Van, Giang Nguyen;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.134-134
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    • 2021
  • Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

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