Jump to ContentJump to Main Navigation

You are looking at 1-10 of 10 items

  • Keywords: Gaussian process x
Clear All Modify Search

View:

TYPICAL VERTEX DEGREES

Mathew Penrose

in Random Geometric Graphs

Published in print:
2003
Published Online:
September 2007
ISBN:
9780198506263
eISBN:
9780191707858
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198506263.003.0004
Subject:
Mathematics, Probability / Statistics

This chapter is concerned with the empirical process of k-nearest neighbour distances for n random points, where k=k(n) is specified and is either fixed or grows with n. That is, the proportion of ... More


What is a random process

Melvin Lax, Wei Cai, and Min Xu

in Random Processes in Physics and Finance

Published in print:
2006
Published Online:
January 2010
ISBN:
9780198567769
eISBN:
9780191718359
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198567769.003.0002
Subject:
Physics, Theoretical, Computational, and Statistical Physics

A random or stochastic process is a random variable that evolves in time by some random mechanism (of course, the time variable can be replaced by a space variable, or some other variable, in ... More


Gaussian Solutions

Gopinath Kallianpur and P. Sundar

in Stochastic Analysis and Diffusion Processes

Published in print:
2014
Published Online:
April 2014
ISBN:
9780199657063
eISBN:
9780191781759
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199657063.003.0009
Subject:
Mathematics, Probability / Statistics, Applied Mathematics

Gaussian solutions of stochastic differential equations play a special role in linear filtering problems. After a discussion of Gohberg-Krein special factorization, its connection to Gaussian ... More


Nonparametric Bayesian machine learning and signal processing

Max A. Little

in Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics

Published in print:
2019
Published Online:
October 2019
ISBN:
9780198714934
eISBN:
9780191879180
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198714934.003.0010
Subject:
Mathematics, Logic / Computer Science / Mathematical Philosophy, Mathematical Physics

We have seen that stochastic processes play an important foundational role in a wide range of methods in DSP. For example, we treat a discrete-time signal as a Gaussian process, and thereby obtain ... More


Optimization Under Unknown Constraints *

Robert B. Gramacy and Herbert K. H. Lee

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0008
Subject:
Mathematics, Probability / Statistics

Optimization of complex functions, such as the output of computer simulators, is a difficult task that has received much attention in the literature. A less studied problem is that of optimization ... More


Gaussian Processes and the Null-Category Noise Model

Lawrence Neil D. and Jordan Michael I.

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0008
Subject:
Computer Science, Machine Learning

This chapter presents an augmentation of the standard probabilistic classification model which incorporates a null-category. Given a suitable probabilistic model for the model category, the chapter ... More


Gaussian Approximation under Asymptotic Negative Dependence

Florence Merlevède, Magda Peligrad, and Sergey Utev

in Functional Gaussian Approximation for Dependent Structures

Published in print:
2019
Published Online:
April 2019
ISBN:
9780198826941
eISBN:
9780191865961
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198826941.003.0009
Subject:
Mathematics, Probability / Statistics

Here we introduce the notion of asymptotic weakly associated dependence conditions, the practical applications of which will be discussed in the next chapter. The theoretical importance of this class ... More


Testing for Neglected Nonlinearity Using Twofold Unidentified Models under the Null and Hexic Expansions

Jin Seo Cho, Isao Ishida, and Halbert White

in Essays in Nonlinear Time Series Econometrics

Published in print:
2014
Published Online:
August 2014
ISBN:
9780199679959
eISBN:
9780191760136
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199679959.003.0001
Subject:
Economics and Finance, Econometrics

We revisit the twofold identification problem discussed by Cho, Ishida, and White (2011), which arises when testing for neglected nonlinearity by artificial neural networks. We do not use the ... More


Markov Random Fields on Undirected Graphs

Ulf Grenander and Michael I. Miller

in Pattern Theory: From representation to inference

Published in print:
2006
Published Online:
November 2020
ISBN:
9780198505709
eISBN:
9780191916564
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198505709.003.0005
Subject:
Computer Science, Programming Languages

This chapter focuses on random fields on lattices and undirected graphs. Discrete finite state spaces are examined in the context of Markov and Gibbs fields. The ... More


Cokriging

Vera Pawlowsky-Glahn and Richardo A. Olea

in Geostatistical Analysis of Compositional Data

Published in print:
2004
Published Online:
November 2020
ISBN:
9780195171662
eISBN:
9780197565513
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780195171662.003.0011
Subject:
Earth Sciences and Geography, Geophysics: Earth Sciences

The problem of estimation of a coregionalization of size q using cokriging will be discussed in this chapter. Cokriging—a multivariate extension of kriging—is the ... More


View: