It is shown that the global power function of any nonparametric test is at on balls of alternatives except for alternatives coming from a nite dimensional sub-space. The present benchmark is here the upper one-sided (or two-sided) envelope power function. It turns out that also the level points are far away from the corresponding Neyman Pearson test level points except for a nite number of orth...

Frequentist statistics is often applied in the framework of null hypothesis significance testing (NHST). We will look at the Neyman-Pearson paradigm which focuses on one hypothesis called the null hypothesis: for example, that the tested treatment has no effect on the progress of the disease. There are other paradigms for hypothesis testing, but NeymanPearson is the most common. Stated simply, ...

We give a description of the steps leading to a robustification of a dose–response study. The original experiment was designed and described by Rosenberger and Grill (1997) and has since been discussed by several other groups of researchers. Our robustification consists of redesigning the experiment so as to build in flexibility over a range of possible link functions, including the logistic li...

In a frequently cited paper, Becker (1974) asked whether data from a “mortal” (= terminated) smallpox outbreak better fit a subcritical or semicritical Galton-Watson branching process. We revisit this question using standard hypothesis-testing methods and reach a somewhat di↵erent conclusion than he did. For a non-terminated process, the related problem of predicting extinction or explosion als...

The Behrens-Fisher problem concerns the inference for the difference between the means of two normal populations whose ratio of variances is unknown. In this situation, Fisher’s fiducial interval differs markedly from the Neyman-Pearson confidence interval. A prior proposed by Jeffreys leads to a credible interval that is equivalent to Fisher’s solution, but carries a different interpretation. ...

A stochastic resonance effect, under the form of a noise-improved performance, is shown feasible for a whole range of optimal detection strategies, including Bayesian, minimum error-probability, Neyman–Pearson, and minimax detectors. In each case, situations are demonstrated where the performance of the optimal detector can be improved (locally) by raising the level of the noise. This is obtain...

Commonly, in accordance with a given risk-function of hypothesis testing, investigators try to derive an optimal property of a test. This paper demonstrates that criteria for which a given test is optimal can be declared by the structure of this test, and hence almost any reasonable test is optimal. In order to establish this conclusion, the principle idea of the fundamental lemma of Neyman and...

The Bayesian time-frequency detector operating on spectrogram of non stationary signals is studied. As direct evaluation of the likelihood ratio is impossible, an a priori user parameter called focus is introduced. It is defined as a local time-frequency signal to noise ratio at which the detection is tuned to be optimal. Leading to a unique detection threshold, the parameter introduced is equi...

Automatic inspection of woven textile fabric is discussed. Two signiicant problems are addressed: (a) texture feature extraction; Fourier transform features are found to be well matched to the spatially periodic nature of the woven pattern; moreover , they are shift invariant; (b) detector design; maximum likelihood type detectors are inappropriate since we cannot hope to enumerate all defect c...

This paper proposes the use of ultrasonic microscale subarrayed MIMO RADARs to estimate the position of breast cancer nodes. The transmit and receive antenna arrays are divided into subarrays. In order to increase the signal diversity each subarray is assigned a different waveform from an orthogonal set. High-frequency ultrasonic transducers are used since a breast is considered to be a superfi...