• Title/Summary/Keyword: Robust Statistics

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Parameters estimation of the generalized linear failure rate distribution using simulated annealing algorithm

  • Sarhan, Ammar M.;Karawia, A.A.
    • International Journal of Reliability and Applications
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    • v.13 no.2
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    • pp.91-104
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    • 2012
  • Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.

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A Study on Teaching Method of One-Sample Test for Population Mean (일표본 모평균 검정의 지도에 관한 연구)

  • 김용택;이장택
    • The Mathematical Education
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    • v.42 no.3
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    • pp.419-423
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    • 2003
  • The main purpose of this paper is to investigate effects of skewness and kurtosis on the one-sample test. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. Also the change of type I error was completely based on skewness under the same size of the sample. We conclude that using t-test is more similar to robust than using z-test. In introductory statistics classes where data analysis includes techniques for detecting skewness, we recommend the t-test when skewness is smaller than the value 1 to the one-sample test for a mean when the variances is unknown using the probability of a type I error as the criterion of interest.

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Robust Watermarking based on HVS statistics and Frequency domain (HVS 특성 및 주파수 공간 특성을 이용한 강인한 워터마킹)

  • Kim, Yoon-Ho;Park, Ki-Hong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.300-303
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    • 2005
  • 본 논문에서는 디지털 멀티미디어 데이터의 저작권 보호를 위하여 웨이블릿 기반 인간 시각 시스템과 주파수 계수의 공간적 특성을 이용한 워터마킹 알고리즘을 제안하였다. 원영상을 1-Level 분해하여 HL1영역과 LH1영역을 4${\times}$4 영역으로 블록화하고 각 블록의 엔트로피와 텍스쳐 값이 가장 좋은 영역을 찾는다. 워터마크가 삽입될 영역은 상위 레벨 계수들의 상관도 특성에 따라서 3-Level 영역에 워터마크를 삽입하였다. 성능평가로 JPEG 압축, 필터링 등 워터마크된 영상에 외부공격을 가하여 워터마크 추출여부를 확인하였고, 실험결과 제안한 알고리즘은 JPEG 압축 50% 이상에서 90%이상의 상관도를 보였고, 샤프닝, 필터링 및 부분삭제 영상변형에 강인함을 보였다.

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Statistical Tests for Edg Detection (에지 검출을 위한 통계적 검정법)

  • Im, Dong-Hun;Seong, Sin-Hui
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.3
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    • pp.1021-1024
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    • 2000
  • In this paper we describe a nonparametric Wilcoxon test and a parametric Z test based on statistical hypothesis testing for the detection of edges. We use the threshold determined by specifying significance level $\alpha$, while Bovik, Huang and Munson[4] consider the range of possible values of test statistics for the threshold. From the experimental results of edge detection, the Z method performs sensitively to the noisy image, while the Wilcoxon method is robust over both noisy nd noise-free images. Comparison with our statistical tests and Sobel operator shows that our tests perform more effectively in both noisy and noise-free images.

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Adaptive Blind MMSE Equalization for SIMO Channel

  • Ahn, Kyung-Seung;Baik, Heung-Ki
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.8A
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    • pp.753-762
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    • 2002
  • Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequences, nor dose it require a priori channel information. In this paper, an adaptive blind MMSE channel equalization technique based on second-order statistics in investigated. We present an adaptive blind MMSE channel equalization using multichannel linear prediction error method for estimating cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. Performance of our algorithms and comparisons with existing algorithms are shown for real measured digital microwave channel.

A graphical method for discriminant analysis when covariance matrices are unequal (공분산행렬이 서로 다를 경우 그래프에 의한 판별분석)

  • 김성주;정갑도
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.409-419
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    • 1993
  • This paper concerns graphical methods for discriminant analysis. We discuss Sammon's graph, MV graph and possibility of an alternative. The properties of the three graphs are investigated using real data and simulation studies. Dimensionality reduction for an alternative and robust procedure are discussed.

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A robust method for response variable transformations using dynamic plots

  • Seo, Han Son
    • Communications for Statistical Applications and Methods
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    • v.26 no.5
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    • pp.463-471
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    • 2019
  • The variable transformations are useful ways to guarantee the functional relationships in the model. However, the presence of outliers may undermine the accuracy of transformation. This paper deals with response transformations in the partial linear models under the existence of outliers. A new procedure for response transformation and outliers detection is proposed. The procedure uses a sequential method for identifying outliers and dynamic graphical methods for an appropriate transformation. The graphical tools make it possible to catch diagnostic information by monitoring the movement of points in the data. The procedure is illustrated with several examples. Examples show that visual clues regarding the optimal transformation, the fittness of the model and the outlyness of the observations can be checked from the series of plots.

Benefits and Spillover Effects of Infrastructure: A Spatial Econometric Approach

  • Kim, Kijin;Lee, Junkyu;Albis, Manuel Leonard;Ang, Ricardo III B.
    • East Asian Economic Review
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    • v.25 no.1
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    • pp.3-31
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    • 2021
  • This paper estimates the effects of transport (road and rail) & energy and ICT infrastructure (telephone, mobile, and broadband) on GDP growths in neighboring countries as well as own countries. We confirm positive direct contributions of infrastructure, access to Internet, and human capital on economic growth. The spatial panel regression models indicate that there exist positive externalities of the broadband infrastructure and human capital, and these results are robust regardless of the choice of spatial weight matrices. Our findings on spillover effects of infrastructure suggest the key role of neighboring countries' infrastructure on own country's economic growth.

Semi closed-form pricing autocallable ELS using Brownian Bridge

  • Lee, Minha;Hong, Jimin
    • Communications for Statistical Applications and Methods
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    • v.28 no.3
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    • pp.251-265
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    • 2021
  • This paper discusses the pricing of autocallable structured product with knock-in (KI) feature using the exit probability with the Brownian Bridge technique. The explicit pricing formula of autocallable ELS derived in the existing paper handles the part including the minimum of the Brownian motion using the inclusion-exclusion principle. This has the disadvantage that the pricing formula is complicate because of the probability with minimum value and the computational volume increases dramatically as the number of autocall chances increases. To solve this problem, we applied an efficient and robust simulation method called the Brownian Bridge technique, which provides the probability of touching the predetermined barrier when the initial and terminal values of the process following the Brownian motion in a certain interval are specified. We rewrite the existing pricing formula and provide a brief theoretical background and computational algorithm for the technique. We also provide several numerical examples computed in three different ways: explicit pricing formula, the Crude Monte Carlo simulation method and the Brownian Bridge technique.

Regression discontinuity for survival data

  • Youngjoo Cho
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.155-178
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    • 2024
  • Regression discontinuity (RD) design is one of the most widely used methods in causal inference for estimation of treatment effect when the treatment is created by a cutpoint from the covariate of interest. There has been little attention to RD design, although it provides a very useful tool for analysis of treatment effect for censored data. In this paper, we define the causal effect for survival function in RD design when the treatment is assigned deterministically by the covariate of interest. We propose estimators of this causal effect for survival data by using transformation, which leads unbiased estimator of the survival function with local linear regression. Simulation studies show the validity of our approach. We also illustrate our proposed method using the prostate, lung, colorectal and ovarian (PLCO) dataset.