Results 231 to 240 of about 282,414 (265)
Some of the next articles are maybe not open access.
A non-parametric approach to behavioral device modeling
2010 11th International Symposium on Quality Electronic Design (ISQED), 2010This work proposes a non-parametric methodology for quick and effective behavioral macromodeling of complex digital and analog devices. Gaussian Process Regression (GPR) learning algorithms are used to generate simple, robust, and widely applicable time-domain models without specifying device equations or parameters.
Dragoljub Gagi Drmanac +2 more
openaire +1 more source
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
openaire +1 more source
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.
openaire +1 more source
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.
openaire +1 more source
Non-parametric Spectral Model for Shape Retrieval
2015 International Conference on 3D Vision, 2015Non-rigid 3D shape retrieval is an active and important research topic in content based object retrieval. This problem is often cast in terms of the shapes intrinsic geometry due to its invariance to a wide range of non-rigid deformations. In this paper, we devise a novel generative model for shape retrieval based on the spectral representation of the ...
Andrea Gasparetto +2 more
openaire +1 more source
Simulated Non-Parametric Estimation of Dynamic Models
Review of Economic Studies, 2009Summary: 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, 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
openaire +2 more sources
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
openaire +2 more sources
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 ...
openaire +1 more source
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
openaire +1 more source
Homothetic non-parametric production models
Economics Letters, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Primont, Daniel, Primont, Diane
openaire +1 more source