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Showing 1 to 20 of 387 for “"Hypothesis testing"”.
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Applications in Quantum Hypothesis Testing
L'abstract è presente nell'allegato / the abstract is in the attachment
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Frugal hypothesis testing and classification
The design and analysis of decision rules using detection theory and statistical learning theory is important because decision making under uncertainty is pervasive. Three perspectives on limiting the complexity of decision rules are considered in this thesis: geometric regularization, …
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Mismatched divergence and universal hypothesis testing
Item reinstated by Sarah Shreeves (sshreeve@illinois.edu) on 2012-01-07T11:00:14Z Item was in collections: Dissertations and Theses - Electrical and Computer Engineering (ID: 446) University of Illinois Dissertations and Theses (ID: 204) No. of bitstreams: 3 Huang_Dayu.pdf.txt: 77576 bytes, …
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Statistical Hypothesis Testing Under Model Uncertainty
Statistical testing is one of the main problems in statistics and finds applications in a number of fields, including engineering, signal processing, medicine, and finance among others. Traditionally in hypothesis testing problem, the hypothesis distributions subject to testing are known. However, …
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Data selection in binary hypothesis testing
… for data selection combined with binary hypothesis testing. We develop models for data selection in several cases, considering both random and deterministic approaches. Our considerations are divided into two classes depending upon the amount of information available about the competing …
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SEQUENTIAL METHODS FOR NON-PARAMETRIC HYPOTHESIS TESTING
… such algorithms for two-sided sequential binary hypothesis testing.</p> <p>In this dissertation, we propose two algorithms for sequential non-parametric hypothesis testing. The proposed algorithms are based on the random distortion testing (RDT) framework. The RDT framework addresses the problem …
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Hypothesis testing and learning with small samples
Made available in DSpace on 2013-02-03T19:47:07Z (GMT). No. of bitstreams: 2 Dayu_Huang.pdf: 867949 bytes, checksum: 1380ac54cb65b4bf5dc75aac2c9cb8dc (MD5) license.txt: 4059 bytes, checksum: 77c2d693fd71ccd7d98454f2a06de3cb (MD5)
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Distributed nonparametric training algorithms for hypothesis testing networks
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Decentralized decision making in a hypothesis testing environment
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.
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Hypothesis testing procedures for non-nested regression models
… several new approaches have been developed for testing non-nested regression models. A comprehensive review of the procedures for the case of two linear regression models was presented. Comparisons between these procedures were made on the basis of asymptotic distributional properties, simulated …
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Hypothesis Testing Using Spatially Dependent Heavy-Tailed Multisensor Data
<p>The detection of spatially dependent heavy-tailed signals is considered in this dissertation. While the central limit theorem, and its implication of asymptotic normality of interacting random processes, is generally useful for the theoretical characterization of a wide variety of natural and …
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LINEAR HYPOTHESIS TESTING FOR HIGH-DIMENSIONAL DATA UNDER HETEROSCEDASTICITY
… we mainly consider three high-dimensional hypothesis testing problems: the two-sample Behrens-Fisher problem, the heteroscedastic one-way MANOVA, and the general linear hypothesis under heteroscedasticity. Although these problems have been thoroughly studied in the classical setting, …
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Universal outlier hypothesis testing with applications to anomaly detection
Outlier hypothesis testing is studied in a universal setting. Multiple sequences of observations are collected, a small subset (possibly empty) of which are outliers. A sequence is considered an outlier if the observations in that sequence are distributed according to an “outlier” distribution, …
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Order-constrained inference: a nuanced approach to hypothesis testing
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Hypothesis testing and causal inference with heterogeneous medical data
… techniques may broaden the fields of hypothesis testing and causal inference to handle the subtleties of large heterogeneous data sets, as well as simultaneously improve the robustness and theoretical understanding of machine learning algorithms using insights from causality and …
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Auditor Mental Representations and Hypothesis Testing of the Control Environment
… utilize a diagnostic and/or a conservative hypothesis testing strategy when testing client management’s ethicality and competence as these are fundamental components of the client’s control environment. A diagnostic testing strategy is evidenced by the auditor searching for the most …
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Likelihood-Free Hypothesis Testing and Applications of the Energy Distance
This thesis studies questions in nonparametric testing and estimation that are inspired by machine learning. One of the main problems of our interest is likelihood-free hypothesis testing: given three samples X, Y and Z with sample sizes n, n and m respectively, one must decide whether the …
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Composite Likelihood: Multiple Comparisons and Non-Standard Conditions in Hypothesis Testing
… the dimension. We study the problem of multiple hypothesis testing for multidimensional clustered data. The problem of multiple comparisons is common in many applications. We propose to construct multiple comparisons procedures based on composite likelihood statistics. The simultaneous …
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Controlling for confounding network properties in hypothesis testing and anomaly detection
… of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like …
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Multiscale hypothesis testing with application to anomaly characterization from tomographic projections
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
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