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Modeling by Non-Parametric Regression
1997In the previous chapter on the adaptive modeling of natural laws it was stated that tasks associated with such modeling included the estimation and storage of the probability distribution, as well as the development of a method for its effective application.
Igor Grabec, Wolfgang Sachse
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Random effects models with non‐parametric priors
Statistics in Medicine, 1992AbstractWe discuss the performance of non‐parametric maximum likelihood (NPML) estimators for the distribution of a univariate random effect in the analysis of longitudinal data. For continuous data, we analyse generated and real data sets, and compare the NPML method to those that assume a Gaussian random effects distribution and to ordinary least ...
S M, Butler, T A, Louis
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2001
This chapter presents a range of statistical techniques that are available for the analysis of word frequency distributions. Section 2.1 introduces some basic probabilistic concepts. Section 2.2 discusses the urn model, according to which word use is viewed as random selection from a population with fixed probabilities for words to occur.
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This chapter presents a range of statistical techniques that are available for the analysis of word frequency distributions. Section 2.1 introduces some basic probabilistic concepts. Section 2.2 discusses the urn model, according to which word use is viewed as random selection from a population with fixed probabilities for words to occur.
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A non-parametric Bayesian model for bounded data
Pattern Recognition, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thanh Minh Nguyen 0001 +1 more
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Non-parametric habitat models with automatic interactions
Journal of Vegetation Science, 2006AbstractQuestions:Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods?Methods:Non‐parametric multiplicative regression (NPMR ...
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Homothetic non-parametric production models
Economics Letters, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Primont, Daniel, Primont, Diane
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Non-parametric models for spatial efficiency
Journal of Productivity Analysis, 1995This research develops a nonconvex model for measuring the spatial efficiency of siting decisions and demonstrates the virtues of such measurements in comparison to those of convex approaches. Working with a case study from the public sector, we develop relative spatial efficiency (RSE) models which access the sufficiency of a location decision in ...
Antreas D. Athanassopoulos +1 more
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A non-parametric model for Ballistocardiography
2014 IEEE Workshop on Statistical Signal Processing (SSP), 2014Yu Yao +3 more
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Local Likelihood for Non-Parametric ARCH(1) Models
SSRN Electronic Journal, 2003Abstract. We propose a non‐parametric local likelihood estimator for the log‐transformed autoregressive conditional heteroscedastic (ARCH) (1) model. Our non‐parametric estimator is constructed within the likelihood framework for non‐Gaussian observations: it is different from standard kernel regression smoothing, where the innovations are assumed to ...
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