Topic
Statistical hypothesis testing
About: Statistical hypothesis testing is a research topic. Over the lifetime, 19580 publications have been published within this topic receiving 1037815 citations. The topic is also known as: statistical hypothesis testing & confirmatory data analysis.
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Book•
01 Jun 1997
TL;DR: Basic Principles of Population Genetics * Counting Methods and the EM Algorithm * Newton's Method and Scoring * Hypothesis Testing and Categorical Data
Abstract: Basic Principles of Population Genetics * Counting Methods and the EM Algorithm * Newton's Method and Scoring * Hypothesis Testing and Categorical Data * Genetic Identity Coefficients * Applications of Identity Coefficients * Computation of Mendelian Likelihoods * The Polygenic Model * Descent Graph Models * Molecular Phylogeny * Radiation Hybrid Mapping * Models of Recombination * Sequence Analysis * Poisson Approximation * Diffusion Processes
389 citations
27 Jul 2002
TL;DR: A model independent procedure for verifying properties of discrete event systems based on Monte Carlo simulation and statistical hypothesis testing that is probabilistic in two senses and carried out in an anytime manner.
Abstract: We propose a model independent procedure for verifying properties of discrete event systems The dynamics of such systems can be very complex, making them hard to analyze, so we resort to methods based on Monte Carlo simulation and statistical hypothesis testing The verification is probabilistic in two senses First, the properties, expressed as CSL formulas, can be probabilistic Second, the result of the verification is probabilistic, and the probability of error is bounded by two parameters passed to the verification procedure The verification of properties can be carried out in an anytime manner by starting off with loose error bounds, and gradually tightening these bounds
389 citations
Book•
01 Jan 1993TL;DR: In this paper, the asymptotic distribution of the QMLE and the information matrix equality is analyzed. And the Radon-Nikodym theorem and central limit theorem are discussed.
Abstract: 1. Introductory remarks 2. Probability densities, likelihood functions and the quasi-maximum likelihood estimator 3. Consistency of the QMLE 4. Correctly specified models of density 5. Correctly specified models of conditional expectation 6. The asymptotic distribution of the QMLE and the information matrix equality 7. Asymptotic efficiency 8. Hypothesis testing and asymptotic covariance matrix estimation 9. Specification testing via m-tests 10. Applications of m-testing 11. Information matrix testing 12. Conclusion Appendix 1. Elementary concepts of measure theory and the Radon-Nikodym theorem Appendix 2. Uniform laws of large numbers Appendix 3. Central limit theorems.
387 citations
TL;DR: It seems that simplicity and parsimony may be an additional factor in managing these errors, in which case the standard methods of model selection are incomplete implementations of Occam's razor.
386 citations
Posted Content•
TL;DR: The Jobson-Korkie-test of equal Sharpe ratios as discussed by the authors is widely used in the performance evaluation literature and it has been shown that the test statistic can be simplified without loss of its statistical properties.
Abstract: The Jobson-Korkie-test of equal Sharpe Ratios is widely used in the performance evaluation literature. This letter has two purposes: First, it corrects a typographical error in the test statistic. Second, it shows that the test statistic can be simplified without loss of its statistical properties.
385 citations