An adaptive two-sample location-scale test of lepage type for symmetric distributions

Büning, Herbert; Thadewald, Thorsten

doi:10.1080/00949650008812003

Cited by 38 publications

(15 citation statements)

References 37 publications

(4 reference statements)

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“…For a specific alternative hypothesis, there is no clear winner in test performance among all the nonparametric tests, and the efficiency of all the tests depends on the types of the underlying distributions. For example, for symmetric distributions with the same shape parameters, the Lepage-type tests are the best [48], [51], whereas for extremely right-skewed distributions, a modification of the KS test behaves better [48], [49]. Therefore, an "adaptive" procedure should be applied for selecting the most suitable test for a given data set.…”

Section: B Pixel Clustering: Adaptive Two-sample Hypothesis Testmentioning

confidence: 95%

Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR

Jiang

Ding

2014

IEEE Trans. Geosci. Remote Sensing

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The coherence of radar echoes is a fundamental observable in interferometric synthetic aperture radar (InSAR) measurements. It provides a quantitative measure of the scattering properties of imaged surfaces and therefore is widely applied to study the physical processes of the Earth. However, unfortunately, the estimated coherence values are often biased due to various reasons such as radar signal nonstationarity and the bias in the estimators used. In this paper, we focus on multitemporal InSAR coherence estimation and present a hybrid approach that mitigates effectively the errors in the estimation. The proposed approach is almost completely self-adaptive and workable for both Gaussian and non-Gaussian SAR scenes. Moreover, the bias of the sample coherence can be mitigated with even only several samples included for a given pixel. Therefore, it is a more pragmatic method for accurate coherence estimation and can be applied actually. Different data sets are used to test the proposed method and demonstrate its advantages.Index Terms-Adaptive hypothesis test, bootstrap, coherence estimation, fringe rate estimation, interferometric synthetic aperture radar (InSAR).

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Section: B Pixel Clustering: Adaptive Two-sample Hypothesis Testmentioning

confidence: 95%

Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR

Jiang

Ding

2014

IEEE Trans. Geosci. Remote Sensing

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“…The Lepage test behaves well for symmetric and medium-to heavy-tailed distributions. After the Lepage test was proposed, numerous discussions followed, e.g., Pettitt (1976); Büning and Thadewald (2000); Neuhäuser (2000); Bün-ing (2002); Murakami (2007), with variations on the Lepage-type test proposed.…”

Section: The Mood Test Namely T M Is Given Bymentioning

confidence: 99%

A moment generating function of a combination of linear rank tests and its asymptotic efficiency

Murakami

2016

TEST

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When testing hypotheses in two-sample problems, the Lepage test has often been used to jointly test the location and scale parameters, and has been discussed by many authors over the years. The Lepage test was a combination of the Wilcoxon statistic and the Ansari-Bradley statistic. Various Lepage-type tests were proposed with discussions of an asymptotic relative efficiency (Duran et al., Biometrika 63:173-176, 1976; Goria, Stat Neerl 36:3-13, 1982), a robustness and a power comparison (Neuhäuser, Commun Stat Theory Methods 29:67-78, 2000; Büning, J Appl Stat 29:907-924, 2002) and an adaptive test (Büning and Thadewald, J Stat Comput Sim 65: 2000). We derive an expression for the moment generating function of a linear combination of two linear rank statistics. As a suggested Lepage-type test, we use a combination of the generalized Wilcoxon statistic and the generalized Mood statistic. Deriving the exact critical value of the statistic can be difficult when the sample sizes are increasing. In this situation, an approximation method to the distribution function of the test statistic can be useful with a higher order moment. We use a momentbased approximation with an adjusted gamma polynomial to evaluate the upper tail probability of a Lepage-type test for a finite sample size. We determine the asymptotic efficiencies of the Lepage and Lepage-type tests for various distributions.

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“…Yonetani [17][18][19] and Nakazawa and Rajendran [20] studied to detect the changes by using the Lepage test. After the Lepage test was proposed, various Lepagetype statistics have been proposed and discussed over the course of many years, e.g., Büning and Thaewald [21], Neuhäuser [22], Büning [23], Murakami [24]. One of the most famous and powerful Lepage-type statistic is a combination of the Wilcoxon and Mood [25] statistics, namely V, proposed by Pettitt [26].…”

Section: Introductionmentioning

confidence: 99%

A nonparametric location–scale statistic for detecting a change point

Murakami

2011

Int J Adv Manuf Technol

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The nonparametric location-scale statistic is introduced for a change-point problem. A combination of the Wilcoxon and Mood statistics is extended to the change-point setting. The limiting distribution of proposed statistic is derived for testing the null hypothesis of no change. The finite sample critical value of the suggested statistic is estimated by simulation studies. The accuracy of detecting a change point is investigated by simulation studies for various distributions. The method is illustrated by the analysis of real data.

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An adaptive two-sample location-scale test of lepage type for symmetric distributions

Cited by 38 publications

References 37 publications

Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR

Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR

A moment generating function of a combination of linear rank tests and its asymptotic efficiency

A nonparametric location–scale statistic for detecting a change point

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