• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.1-12
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• 1995

Let F be a life distribution with finite mean $\mu$ Then F is said to be in new better then worse than used in expectation (NBWUE(p)) class if $\varphi(u) {\geq} u$ for $0 {\leq}u{\leq}t_0$ and ${\varphi}(u) {\leq} u$ for $t_0< u {\leq} 1$ where ${\varphi}(u)$ is the scaled total-time-on-test transform and $p=F(t_0)$. We propose a testing procedure for $H_0$ : F is exponential against $H_1$ : NBWUE(p), and is not expontial, (or $H_1\;'$ : F is NWBUE (p), and is not exponential) using randomly censored data. Our procedure assumes kmowledge of the proportion p of the population that fail at or before the change-point $\t_0$. Know ledge of $\t_0$ itself is not assumed. The asymptotic normality of the test statistic is established and a Monte Carlo experiment is performed to investigate the speed of convergence of the test statistic to normality. The power of our test is also studied.

• Communications for Statistical Applications and Methods
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• 제17권6호
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• pp.829-843
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• 2010

To test for the serial dependence in time series of counts data, Jung and Tremayne (2003) evaluated the size and power of several tests under the class of INARMA models based on binomial thinning operations for Poisson marginal distributions. The overdispersion phenomenon(i.e., a variance greater than the expectation) is common in the real world. Overdispersed count data can be modeled by using alternative thinning operations such as random coefficient thinning, iterated thinning, and quasi-binomial thinning. Such thinning operations can lead to time series models of counts with negative binomial or generalized Poisson marginal distributions. This paper examines whether the test statistics used by Jung and Tremayne (2003) on serial dependence in time series of counts data are affected by overdispersion.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.301-317
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• 2022

In this paper, we propose a change point detection procedure based on the modified information criterion in a generalized lambda distribution (GLD) model. Simulations are conducted to obtain empirical critical values of the proposed test statistic. We have also conducted simulations to evaluate the performance of the proposed methods comparing to the log-likelihood method in terms of power, coverage probability, and confidence sets. Our results indicate that, under various conditions, the proposed method modified information criterion (MIC) approach shows good finite sample properties. Furthermore, we propose a new goodness-of-fit testing procedure based on the energy distance to evaluate the asymptotic null distribution of our test statistic. Two real data applications are provided to illustrate the use of the proposed method.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.397-412
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• 2020

In this paper, a notion of data depth is used to propose nonparametric multivariate two sample tests for difference between scale parameters. Data depth can be used to measure the centrality or outlying-ness of the multivariate data point relative to data cloud. A difference in the scale parameters indicates the difference in the depth values of a multivariate data point. By observing this fact on a depth vs depth plot (DD-plot), we propose nonparametric multivariate two sample tests for scale parameters of multivariate distributions. The p-values of these proposed tests are obtained by using Fisher's permutation approach. The power performance of these proposed tests has been reported for few symmetric and skewed multivariate distributions with the existing tests. Illustration with real-life data is also provided.

• Journal of the Korean Statistical Society
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• 제22권1호
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• pp.113-124
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• 1993

In this paper we show that the results of Ahn and Cho (1992) can be applied to a more general class of seasonal models, especially models with autocorrelated errors. Employing the idea of the "two-step estimation" method, we provide test statistics which are easy to compute and have the same asymptotic properties as those in Ahn and Cho (1992) for seasonal unit roots. A numerical example is presented to illustrate the methods and concepts. The power of the test statistics for finite samples is examined through a Monte Carlo sampling experiment.xperiment.

• Journal of the Korean Statistical Society
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• 제27권2호
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• pp.165-187
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• 1998

Shin and Sarkar (1993, 1994) studied the problem of testing for a unit root in an AR(p) signal observed with MA(q) noise when the MA parameters are known. In this paper we consider the case when the MA parameters are unknown and to be estimated. Test statistics are defined using unit root parameter estimates based on three different estimation methods of Hannan and Rissanen (1982), Kohn (1979) and Shin and Sarkar (1995). An AR(p) process contaminated by MA(q) noise is a .estricted ARMA model, for which Shin and Sarkar (1995) derived an easy-to-compute Newton- Raphson estimator The two-stage estimation p.ocedu.e of Hannan and Rissanen (1982) is used to compute initial parameter estimates in implementing the iterative estimation methods of both Shin and Sarkar (1995) and Kohn (1979). In a simulation study we compare the relative performance of these unit root tests with respect to both size and power for p=q=1.

• 응용통계연구
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• 제24권2호
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• pp.383-391
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• 2011

이 논문에서는 역가우스분포의 적합을 위한 변형된 엔트로피 기반 검정을 제시한다. 이 검정은 자료생성분포와 역가우스분포의 엔트로피 차이에 기초를 두고 있으며 검정통계량은 엔트로피 차이의 추정량을 사용한다. 엔트로피 차이의 추정량은 자료생성분포에 대한 엔트로피 추정량으로 Vasicek의 표본엔트로피와 역가우스분포에 대한 엔트로피 추정량로 균일최소분산불편추정량을 사용하여 얻는다. 모의실험을 통해 얻은 표본크기와 윈도크기에 따른 검정통계량의 기각값들을 표의 형태로 제공한다. 제안한 검정의 검정력 알아보기 위해 여러 대립분포와 표본크기에 대해서 모의실험을 수행하고 기존의 엔트로피 기반 검정과 비교한다.

• 응용통계연구
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• 제11권2호
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• pp.257-268
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• 1998

역학연구에서 두 수준을 갖는 위험인자 X와 이항 반응변수 Y의 관계에 관심을 갖는 경우가 많다. 이 때 두 변수의 상관관계에 영향을 미칠 수 있는 인자 Z의 값을 제어함에 따라 X와 Y의 상관관계가 여전히 존재하는지를, 즉 X와 Y의 조건부 독립성을 검정할 필요가 있다 관측값의 수가 많지 않을 때, X와 Y의 조건부 독립성 검정을 위해 Mantel-Haenszel 검 정 이 널리 사용되고 있다. 하지 만 X와 Y의 상관관계가 Z의 수준에 따라 그 방향까지 변할 경우 이 검정은 낮은 검정력을 갖는다. 본 연구에서는 이 경우에 높은 검정력을 갖는 대안 검정통계량을 제안한다. 대안 검정통계량의 분포에 대해 알아보고 모의실험을 통해 Mantel-Haenszel 검정과 비교해 본다.

• 응용통계연구
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• 제6권2호
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• pp.289-302
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• 1993

본 연구에서는 지수분포성 적합도검정 문제를 다루는데, 모수가 미지인 상황에서 제1종단일 우측중도절단 표본과 제2종우측중도절단 표본인 경우에 각각 적용될 수 있는 새로운 검정통 계량을 제안하였다. 미지의 모수 문제를 해결하기 위해서 K-변환을 고려하였으며 중도절단 균일표본을 완결 균일표본으로 전환시키기 위해서 Rosenblatt 변환을 적용하였다. 전환된 완결 균일표본의 적합도검정을 위한 통계량은 분포함수와 경험분포함수의 편차의 $L_1-norm$ 으로 정의되었다. 검정 통계량의 임계치는 Monte Carlo simulation에 의해 구 했으며, 잘 알려진 Pettit 검정법과 검정력을 비교하였는데, 새로 제안된 검정통계량의 검정 력이 대체로 우수한 것으로 평가되었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.