• 제목/요약/키워드: Kolmogorov test

검색결과 228건 처리시간 0.026초

Kolmogorov-Smirnov Type Test for Change with Sample Fourier Coefficients

  • Kim, Jae-Hee
    • Journal of the Korean Statistical Society
    • /
    • 제25권1호
    • /
    • pp.123-131
    • /
    • 1996
  • The problerm of testing for a constant mean is considered. A Kolmogorov-Smirnov type test using the sample Fourier coefficients is suggested and its asymptotic distribution is derived. A simulation study shows that the proposed test is more powerful than the cusum type test when there is more than one change-point or there is a cyclic change.

  • PDF

임펄스성 잡음의 유무를 결정하는 Kolmogorov-Smirnov 검증의 수치적 접근의 효율성 (Numerical Approach with Kolmogorov-Smirnov Test for Detection of Impulsive Noise)

  • 오형국;남해운
    • 한국통신학회논문지
    • /
    • 제39C권9호
    • /
    • pp.852-860
    • /
    • 2014
  • 본 논문에서 임펄스성 잡음의 유무를 검증하는 알고리즘을 제안한다. 본 알고리즘을 제안하는 이유는 기존의 Kolmogorov-Smirnov 검증의 단점으로 낮은 분류 성공률 및 높은 복잡도가 있기 때문이다. 이는 이론적으로 문제가 없으나 실제로 구현함에 있어 많은 문제를 야기한다. 먼저 기존의 검증 방법을 설명 후 제안하는 알고리즘을 설명한다. 이 알고리즘은 기존의 Kolmogorov-Smirnov 검증 방법의 이론적 배경으로부터 제안된다. 알고리즘의 효율성을 증명하기 위해 임펄스성 잡음의 샘플을 이용하여 실험 후, 검증 실패 확률을 조사한다. 검증 실패 확률에 기반한 실험 결과는 제안한 알고리즘의 효율성을 증명한다.

영상에서 에지 검출을 위한 통계적 방법 (Statistical methods for Edge Detection in Images)

  • 임동훈;박은희
    • 응용통계연구
    • /
    • 제13권2호
    • /
    • pp.515-523
    • /
    • 2000
  • 본 논문에서는 변화점 문제(change-point problem)에 대한 통계적 방법들을 사용하여 에지를 검출하고자 한다. 이를 위해 $n\timesn$ 부분영상을 선택하고 선택된 영상이 농도값에서 유의한 차이가 있는 두 개의 영역으로 분할하는 경계에 대응되는 에지점(edge point)을 포함하는지에 대해 가설 검정을 한다. 에지 검출에 사용되는 통계적 방법은 이표본 Kolmogorov-Smirnov 검정에 기초해서 얻은 제안된 방법과 기존의 우도비(likelihood ratio)방법,비모수적인 Wolfe-Schechtman 방법 등이다. 위 방법들의 성능을 평가하기 위해 접음영상과 잡음없는 영상에 대해 실험을 실시하고 비교 분석한다.

  • PDF

Test for the Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Lee, Sang-Ki
    • Communications for Statistical Applications and Methods
    • /
    • 제13권3호
    • /
    • pp.537-550
    • /
    • 2006
  • In this paper, we develope three modified empirical distribution function type tests, the modified Cramer-von Mises test, the modified Anderson-Darling test, and the modified Kolmogorov-Smirnov test for the two-parameter exponential distribution with unknown parameters based on multiply Type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

Bootstrap Tests for the General Two-Sample Problem

  • 조길호;정성화
    • Journal of the Korean Data and Information Science Society
    • /
    • 제13권1호
    • /
    • pp.129-137
    • /
    • 2002
  • Two-sample problem is frequently discussed problem in statistics. In this paper we consider the hypothese methods for the general two-sample problem and suggest the bootstrap methods. And we show that the modified Kolmogorov-Smirnov test is more efficient than the Kolmogorov-Smirnov test.

  • PDF

A Kolmogorov-Smirnov-Type Test for Independence of Bivariate Failure Time Data Under Independent Censoring

  • Kim, Jingeum
    • Journal of the Korean Statistical Society
    • /
    • 제28권4호
    • /
    • pp.469-478
    • /
    • 1999
  • We propose a Kolmogorov-Smirnov-type test for independence of paired failure times in the presence of independent censoring times. This independent censoring mechanism is often assumed in case-control studies. To do this end, we first introduce a process defined as the difference between the bivariate survival function estimator proposed by Wang and Wells (1997) and the product of the product-limit estimators (Kaplan and Meier (1958)) for the marginal survival functions. Then, we derive its asymptotic properties under the null hypothesis of independence. Finally, we assess the performance of the proposed test by simulations, and illustrate the proposed methodology with a dataset for remission times of 21 pairs of leukemia patients taken from Oakes(1982).

  • PDF

신용평가를 위한 Kolmogorov-Smirnov 수정통계량 (Modified Kolmogorov-Smirnov Statistic for Credit Evaluation)

  • 홍종선;방글
    • 응용통계연구
    • /
    • 제21권6호
    • /
    • pp.1065-1075
    • /
    • 2008
  • 신용평가모형 개발과 적합성 검정 연구에서 부도율분포로부터 부도기업과 정상기업의 판별력을 검정하는 방법으로 비모수적인 방법인 Kolmogorov-Smirnov(K-S) 검정방법을 많이 사용한다. 모집단에 대한 누적분포함수를 알고있으며 이 분포함수가 두 개의 분포함수로 분할되었다는 가정하에서 두 분포함수 동일성을 검정하는 신용평가 연구에서 스코어 또는 부도율이 다양한 확률분포를 따른다고 가정하고 기존의 K-S 통계량과 수정된 K-S 통계량을 비교 토론한다.

Closeness of Lindley distribution to Weibull and gamma distributions

  • Raqab, Mohammad Z.;Al-Jarallah, Reem A.;Al-Mutairi, Dhaifallah K.
    • Communications for Statistical Applications and Methods
    • /
    • 제24권2호
    • /
    • pp.129-142
    • /
    • 2017
  • In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

Independence test of a continuous random variable and a discrete random variable

  • Yang, Jinyoung;Kim, Mijeong
    • Communications for Statistical Applications and Methods
    • /
    • 제27권3호
    • /
    • pp.285-299
    • /
    • 2020
  • In many cases, we are interested in identifying independence between variables. For continuous random variables, correlation coefficients are often used to describe the relationship between variables; however, correlation does not imply independence. For finite discrete random variables, we can use the Pearson chi-square test to find independency. For the mixed type of continuous and discrete random variables, we do not have a general type of independent test. In this study, we develop a independence test of a continuous random variable and a discrete random variable without assuming a specific distribution using kernel density estimation. We provide some statistical criteria to test independence under some special settings and apply the proposed independence test to Pima Indian diabetes data. Through simulations, we calculate false positive rates and true positive rates to compare the proposed test and Kolmogorov-Smirnov test.