... Finally, resampling methods for **hypothesis** **testing** were studied in Meinshausen and B¨ uhlmann (2010); Minnier et al. (2011). These methods are perturbation-based procedures to approximate the distribution ...

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... the **hypothesis**-generating study, we have distinct approaches for variants in known disease-causing genes versus variants in genes that are hypothesized to cause disease (the latter being the operative ...

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... Abstract—Binary **hypothesis** **testing** over single and parallel cascade channels is considered where sensors communicate with dedicated relays, and these relays with a single final ...binary **hypothesis** ...

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... Statistical inference involves two analysis methods: estimation and **hypothesis** **testing**, the latter of which is the subject of this article. Specifically, Z tests of proportion are highlighted and ...

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... As a result of an NMA, point estimates with credible intervals of pairwise effects between treatment arms are obtained. In this article, we focus on the issue of **testing** for superiority or noninferiority between ...

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... C. **Hypothesis** **testing** with a 1-bit communication constraint The exponent E in (3) is related to **hypothesis** **testing** under the communication constraint ...

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... Abstract. Information contained in a sample of quantitative data may be summarized or described by a nonparametric histogram density function. An interesting question is how to construct such a histogram density to ...

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... ity **hypothesis** graph of cartilage degradation during to osteoarthritis, and to validate our methodology for confi- dence assessment of causality ...shared **hypothesis** **testing** could be incorporated as ...

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... We consider the asymmetric formulation of quantum **hypothesis** **testing**, where two quantum hypotheses have different associated costs. In this problem, the aim is to minimize the probability of false negatives ...

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... Nevertheless, **testing** the hypothe- sis that the generating distributions of two sets of curves are identical, when the observed data are noisy and discrete realizations of the curves, has received very little ...

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... In this section we review Type II errors briefly. A de- tailed discussion of Type II errors (and **hypothesis** **testing** in general) can be found in any mathematical statistics text, for example, [2]. We assume ...

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... in **hypothesis** **testing**, we collect data to show that the null **hypothesis** is not true, based on the likelihood of selecting a sample mean from a population (the likelihood is the ...null ...

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... predictor. **Hypothesis** **testing** can provide a scientifically rigorous approach to determine which tract profiles are related to ...Additionally, **testing** can determine if modeling the full tract profile ...

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... corroborated **hypothesis** (Mynatt et al., 1978). Perhaps it is only when a **hypothesis** worth **testing** has been established that it is necessary to attempt to falsify ...

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... There are many types of methods for **hypothesis** **testing** in mathematical and statistical analyses. From these methods, T-stat and F-stat are widely used. However, they are in sufficient to express the final ...

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... While it is not the point of this section to discuss empty rectangular sets, it is impor- tant to report the interesting results of the simulations. Unlike any of the other examples, an empty rectangular set was produced ...

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... More importantly, there are often many ways to specify a bootstrap DGP. Whether a bootstrap test works well or badly depends on how well the bootstrap DGP mimics the essential features of the true DGP under the null ...

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... As seen from Table 3 when the sample sizes are small, no procedure managed to attain the correct size. The F calibration of the empirical likelihoods and bootstrap calibration of all tests decreased the Type I error, yet ...

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... So we ask the t test for Paired-Samples t test, which gives t = -2.299. Looking at the next Sig. (2-tailed) the value is .047, lower than proposed. As our **hypothesis** is unilateral divide by 2 and get the ...

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... In this section we consider the effect of ρ > 0 on the test functions in Section 2. For this purpose we change ρ in the interval [0,1) and by simulation we study the robustness of these test functions. A good test ...

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