Results 281 to 290 of about 17,207,506 (302)

Simulated Non-Parametric Estimation of Dynamic Models

Review of Economic Studies, 2009
Summary: This paper introduces a new class of parameter estimators for dynamic models, called simulated non-parametric estimators (SNEs). The SNE minimizes appropriate distances between non-parametric conditional (or joint) densities estimated from sample data and non-parametric conditional (or joint) densities estimated from data simulated out of the ...
Filippo Altissimo, Antonio Mele
openaire   +3 more sources

Random effects models with non‐parametric priors

Statistics in Medicine, 1992
AbstractWe 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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A non-parametric Bayesian model for bounded data

Pattern Recognition, 2015
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Thanh Minh Nguyen 0001, Q. M. Jonathan Wu   +1 more
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Non-parametric habitat models with automatic interactions

Journal of Vegetation Science, 2006
Abstract Questions: 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?
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Non Parametric Models for Covergence Analysis in Europe

2004
[RELAZIONE]
PACINI, BARBARA, PELLEGRINI G.
openaire   +4 more sources

A non-parametric model for Ballistocardiography

2014 IEEE Workshop on Statistical Signal Processing (SSP), 2014
Yu Yao, J. Schiefer, Stefan van Waasen, Michael Schiek   +3 more
openaire   +2 more sources

Local Likelihood for Non-Parametric Arch(1) Models

Journal of Time Series Analysis, 2003
We propose a local likelihood estimation for the log-transformed ARCH(1) model in the financial field. Our nonparametric 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 be normally distributed.
openaire   +2 more sources

Non-Parametric Models

2021
openaire   +1 more source

PaMIR: Parametric Model-Conditioned Implicit Representation for Image-Based Human Reconstruction

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Dai Qionghai, Tao Yu, Zerong Zheng
exaly  

Non Parametric Speech Modeling

Journal of Computational and Theoretical Nanoscience, 2016
openaire   +1 more source