Statistical hypothesis testing in wavelet analysis: theoretical developments and applications to Indian rainfall [PDF]
Nonlinear Processes in Geophysics, 2019 Statistical hypothesis tests in wavelet analysis are methods that assess the degree to which a wavelet quantity (e.g., power and coherence) exceeds background noise. Commonly, a point-wise approach is adopted in which a wavelet quantity at every point in
J. A. Schulte
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Pitfalls of statistical hypothesis testing: multiple testing [PDF]
BMJ, 2014 The effectiveness of a home based intervention on children’s body mass index (BMI) at age 2 years was investigated. A randomised controlled superiority trial was used. The intervention consisted of eight home visits from specially trained community nurses in the first 24 months after birth.
P. Sedgwick
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Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference [PDF]
Machine Learning and Knowledge Extraction, 2019 Statistical hypothesis testing is among the most misunderstood quantitative analysis methods from data science. Despite its seeming simplicity, it has complex interdependencies between its procedural components. In this paper, we discuss the underlying logic behind statistical hypothesis testing, the formal meaning of its components and their ...
Frank Emmert-Streib, Matthias Dehmer
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Errors in Statistical Inference Under Model Misspecification: Evidence, Hypothesis Testing, and AIC
Frontiers in Ecology and Evolution, 2019 The methods for making statistical inferences in scientific analysis have diversified even within the frequentist branch of statistics, but comparison has been elusive.
Brian Dennis +4 more
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Wind Turbine Fault Detection through Principal Component Analysis and Statistical Hypothesis Testing
Energies, 2015 This paper addresses the problem of online fault detection of an advanced wind turbine benchmark under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type: fixed value, gain factor, offset and changed dynamics. The
Francesc Pozo, Yolanda Vidal
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On hypothesis testing for statistical model checking
International Journal on Software Tools for Technology Transfer, 2014 Hypothesis testing is an important part of statistical model checking (SMC). It is typically used to verify statements of the form $p>p_0$ or $p<p_0$, where $p$ is an unknown probability intrinsic to the system model and $p_0$ is a given threshold value. Many techniques for this have been introduced in the SMC literature.
Pieter-Tjerk de Boer +3 more
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Statistical Hypothesis Testing for Postreconstructed and Postregistered Medical Images. [PDF]
SIAM J Imaging Sci, 2009 Demidenko E.
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An Introduction to Statistics: Understanding Hypothesis Testing and Statistical Errors
Indian Journal of Critical Care Medicine, 2019 The second article in this series on biostatistics covers the concepts of sample, population, research hypotheses and statistical errors.Ranganathan P, Pramesh CS. An Introduction to Statistics: Understanding Hypothesis Testing and Statistical Errors. Indian J Crit Care Med 2019;23(Suppl 3):S230-S231.
Priya Ranganathan, CS Pramesh
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Statistical Estimation and Hypothesis Testing on Impulse Response Function
Austrian Journal of StatisticsIn this paper a time-invariant continuous linear system is considered with a real-valued impulse response function (IRF) which is defined on a bounded domain. A sample input- output cross-correlogram is taken as an estimator of the response function.
Iryna Rozora, Anastasiia Melnyk
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Statistical Hypothesis Testing for Asymmetric Tolerance Index
Applied Sciences, 2021 Many of the nominal-the-best quality characteristics of important machine tool components, such as inner or outer diameters, have asymmetric tolerances. An asymmetric tolerance index is a function for the average of the process and the standard deviation.
Kuen-Suan Chen +3 more
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