• In the independent two-sample t-test, we assume normality, independence, and equal variances. • This t-test is robust against nonnormality, but is sensitive to dependence. • If n1 is close to n2, then the test is moderately robust against unequal variance (σ 1 6= σ 2). But if n1 and n2 are quite different (e.g. differ by a ratio of 3 or more), then the test is much less robust. • How to deter...

In this chapter, we will provide an overview of the current status of research involving Bayesian inference in wavelet nonparametric problems. In many statistical applications, there is a need for procedures to (i) adapt to data and (ii) use prior information. The interface of wavelets and the Bayesian paradigm provide a natural terrain for both of these goals.

Abstract The extrapolation of quantiles beyond or below the largest smallest observation plays an important role in hydrological practice, design hydraulic structures, water resources management, risk assessment. Traditionally, extreme are obtained using parametric methods that require to make a priori assumption about distribution generated data. This approach has several limitations mainly wh...

This paper demonstrates that, for large-scale tests, the match and non-match similarity scores have no specific underlying distribution function. The forms of these distribution functions require a nonparametric approach for the analysis of the fingerprint similarity scores. In this paper, we present an analysis of the discrete distribution functions of the match and non-match similarity scores...

the frequency response analysis (fra) test has been recognized as one of the sensitive tools available for detecting electrical and mechanical faults inside power transformers. however, there is still no universally systematic interpretation technique for these tests. many research efforts have employed different statistical criteria in order to aid the interpretative capability of the fra, but...

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