Spatial representation of economic and financial measures used in agriculture via wavelet analysis

Mitchell Morehart, Fionn Murtagh, Jean Luc Starck

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A foundation is set forth for use of the wavelet transform as a spatial analysis tool for modelling the geographical representation of economic and financial measures used in agriculture. This provides a framework from which to estimate a smooth nonparametric function which describes complex, multivariate relationships embedded in spatial data, with the resulting maps conveying large amounts of information in a familiar format. We illustrate this approach for tasks which include the graphical presentation of information, density estimation and wavelet-based nonparametric regression. A redundant wavelet transform is used, and we detail the properties which make it particularly appropriate for these objectives.

Original languageEnglish
Pages (from-to)557-576
Number of pages20
JournalInternational Journal of Geographical Information Science
Volume13
Issue number6
DOIs
Publication statusPublished - 1 Jan 1999
Externally publishedYes

Fingerprint

Wavelet analysis
wavelet analysis
Agriculture
Wavelet transforms
wavelet
agriculture
Economics
Conveying
transform
economics
spatial analysis
spatial data
regression
modeling

Cite this

@article{257cbd1036e248b4baa005312dfb17c0,
title = "Spatial representation of economic and financial measures used in agriculture via wavelet analysis",
abstract = "A foundation is set forth for use of the wavelet transform as a spatial analysis tool for modelling the geographical representation of economic and financial measures used in agriculture. This provides a framework from which to estimate a smooth nonparametric function which describes complex, multivariate relationships embedded in spatial data, with the resulting maps conveying large amounts of information in a familiar format. We illustrate this approach for tasks which include the graphical presentation of information, density estimation and wavelet-based nonparametric regression. A redundant wavelet transform is used, and we detail the properties which make it particularly appropriate for these objectives.",
author = "Mitchell Morehart and Fionn Murtagh and Starck, {Jean Luc}",
year = "1999",
month = "1",
day = "1",
doi = "10.1080/136588199241111",
language = "English",
volume = "13",
pages = "557--576",
journal = "International Journal of Geographical Information Science",
issn = "1365-8816",
publisher = "Taylor and Francis Ltd.",
number = "6",

}

Spatial representation of economic and financial measures used in agriculture via wavelet analysis. / Morehart, Mitchell; Murtagh, Fionn; Starck, Jean Luc.

In: International Journal of Geographical Information Science, Vol. 13, No. 6, 01.01.1999, p. 557-576.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Spatial representation of economic and financial measures used in agriculture via wavelet analysis

AU - Morehart, Mitchell

AU - Murtagh, Fionn

AU - Starck, Jean Luc

PY - 1999/1/1

Y1 - 1999/1/1

N2 - A foundation is set forth for use of the wavelet transform as a spatial analysis tool for modelling the geographical representation of economic and financial measures used in agriculture. This provides a framework from which to estimate a smooth nonparametric function which describes complex, multivariate relationships embedded in spatial data, with the resulting maps conveying large amounts of information in a familiar format. We illustrate this approach for tasks which include the graphical presentation of information, density estimation and wavelet-based nonparametric regression. A redundant wavelet transform is used, and we detail the properties which make it particularly appropriate for these objectives.

AB - A foundation is set forth for use of the wavelet transform as a spatial analysis tool for modelling the geographical representation of economic and financial measures used in agriculture. This provides a framework from which to estimate a smooth nonparametric function which describes complex, multivariate relationships embedded in spatial data, with the resulting maps conveying large amounts of information in a familiar format. We illustrate this approach for tasks which include the graphical presentation of information, density estimation and wavelet-based nonparametric regression. A redundant wavelet transform is used, and we detail the properties which make it particularly appropriate for these objectives.

UR - http://www.scopus.com/inward/record.url?scp=0033396399&partnerID=8YFLogxK

U2 - 10.1080/136588199241111

DO - 10.1080/136588199241111

M3 - Article

VL - 13

SP - 557

EP - 576

JO - International Journal of Geographical Information Science

JF - International Journal of Geographical Information Science

SN - 1365-8816

IS - 6

ER -