Results 241 to 250 of about 349,334 (290)
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IEEE Transactions on Information Theory, 1993
Summary: Burg's standard maximum entropy method and the resulting autoregressive model has been widely applied for spectrum estimation and prediction. A generalization of the maximum entropy formalism in a nonparametric setting is presented, and the class of the resulting solutions is identified to be a class of Markov processes.
Politis, Dimitris Nicolas +1 more
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Summary: Burg's standard maximum entropy method and the resulting autoregressive model has been widely applied for spectrum estimation and prediction. A generalization of the maximum entropy formalism in a nonparametric setting is presented, and the class of the resulting solutions is identified to be a class of Markov processes.
Politis, Dimitris Nicolas +1 more
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Nonparametric Spatial Prediction
Statistical Inference for Stochastic Processes, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Biau, Gérard, Cadre, Benoît
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Nonparametric Background Generation
18th International Conference on Pattern Recognition (ICPR'06), 2006A novel background generation method based on nonparametric background model is presented for background subtraction. We introduce a new model, named as effect components description (ECD), to model the variation of the background, by which we can relate the best estimate of the background to the modes (local maxima) of the underlying distribution ...
Yazhou Liu +4 more
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The American Journal of Occupational Therapy, 1986
Abstract This paper proposes the use of nonparametric statistical methods as a way to increase the quality and quantity of research in occupational therapy. Assumptions underlying parametric versus nonparametric methods are compared and the conditions under which nonparametric methods may be preferred are specified.
C B, Royeen, W L, Seaver
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Abstract This paper proposes the use of nonparametric statistical methods as a way to increase the quality and quantity of research in occupational therapy. Assumptions underlying parametric versus nonparametric methods are compared and the conditions under which nonparametric methods may be preferred are specified.
C B, Royeen, W L, Seaver
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Clinical Pediatrics, 1985
In clinical research, "samples" are studied in order to get ideas about the characteristics of the larger populations from which the samples are taken. Population characteristics are called parameters (the population mean and standard deviation are examples). Parametric statistical methods are those that require estimates of parameters and assumptions
G W, Brown, G F, Hayden
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In clinical research, "samples" are studied in order to get ideas about the characteristics of the larger populations from which the samples are taken. Population characteristics are called parameters (the population mean and standard deviation are examples). Parametric statistical methods are those that require estimates of parameters and assumptions
G W, Brown, G F, Hayden
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NONPARAMETRIC NONSTATIONARITY TESTS
Econometric Theory, 2013We propose additive functional-based nonstationarity tests that exploit the different divergence rates of the occupation times of a (possibly nonlinear) process under the null of nonstationarity (stationarity) versus the alternative of stationarity (nonstationarity). We consider both discrete-time series and continuous-time processes. The discrete-time
Bandi, FM, Corradi, V
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Nonparametric Capability Indices
Economic Quality Control, 2003Summary: The process capability indices \(C_{p}\) and \(C_{pk}\) are widely used in statistical quality control to assess the capability of a process. These indices are defined, based on the assumption that the quality characteristic follows a normal distribution.
Ramanathan, T. V. +2 more
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Nurse Researcher, 2001
This paper by John Belcher aims to give a non-technical illustration of the applications of non-parametric tests and to list the types of medical data that can arise. (In a second paper on pages 26-40, the author presents an overview of time series analysis).
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This paper by John Belcher aims to give a non-technical illustration of the applications of non-parametric tests and to list the types of medical data that can arise. (In a second paper on pages 26-40, the author presents an overview of time series analysis).
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Nonparametric Statistical Inference
International Encyclopedia of Statistical Science, 2020J. Gibbons, S. Chakraborti
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