Zonation of sequences of heteroscedastic multivariate data

Douglas M. Hawkins; J. A. Ten Krooden

doi:10.1016/0098-3004(79)90004-9

Zonation of sequences of heteroscedastic multivariate data

Douglas M. Hawkins, J. A. Ten Krooden

Statistics (Twin Cities)

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

A problem in the earth sciences is to reduce a sequence of observation vectors X₁, X₂, ..., X_N to a set of internally homogeneous segments or zones. This paper uses the model that the observation vectors in the ith zone are a random sample from the multivariate normal N(ξ_i, Σ_i) distribution. It is demonstrated that the maximum likelihood estimates of the boundaries between zones may be determined by dynamic programming, and a FORTRAN algorithm to perform this estimation is given.

Original language	English (US)
Pages (from-to)	189-194
Number of pages	6
Journal	Computers and Geosciences
Volume	5
Issue number	2
DOIs	https://doi.org/10.1016/0098-3004(79)90004-9
State	Published - 1979

Keywords

Dynamic programming
FORTRAN
Heteroscedastic model
Homoscedastic model
Maximum likelihood estimates
Principal components

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10.1016/0098-3004(79)90004-9

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title = "Zonation of sequences of heteroscedastic multivariate data",

abstract = "A problem in the earth sciences is to reduce a sequence of observation vectors X1, X2, ..., XN to a set of internally homogeneous segments or zones. This paper uses the model that the observation vectors in the ith zone are a random sample from the multivariate normal N(ξi, Σi) distribution. It is demonstrated that the maximum likelihood estimates of the boundaries between zones may be determined by dynamic programming, and a FORTRAN algorithm to perform this estimation is given.",

keywords = "Dynamic programming, FORTRAN, Heteroscedastic model, Homoscedastic model, Maximum likelihood estimates, Principal components",

author = "Hawkins, {Douglas M.} and {Ten Krooden}, {J. A.}",

year = "1979",

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AU - Hawkins, Douglas M.

AU - Ten Krooden, J. A.

PY - 1979

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N2 - A problem in the earth sciences is to reduce a sequence of observation vectors X1, X2, ..., XN to a set of internally homogeneous segments or zones. This paper uses the model that the observation vectors in the ith zone are a random sample from the multivariate normal N(ξi, Σi) distribution. It is demonstrated that the maximum likelihood estimates of the boundaries between zones may be determined by dynamic programming, and a FORTRAN algorithm to perform this estimation is given.

AB - A problem in the earth sciences is to reduce a sequence of observation vectors X1, X2, ..., XN to a set of internally homogeneous segments or zones. This paper uses the model that the observation vectors in the ith zone are a random sample from the multivariate normal N(ξi, Σi) distribution. It is demonstrated that the maximum likelihood estimates of the boundaries between zones may be determined by dynamic programming, and a FORTRAN algorithm to perform this estimation is given.

KW - Dynamic programming

KW - FORTRAN

KW - Heteroscedastic model

KW - Homoscedastic model

KW - Maximum likelihood estimates

KW - Principal components

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DO - 10.1016/0098-3004(79)90004-9

M3 - Article

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SN - 0098-3004

VL - 5

SP - 189

EP - 194

JO - Computers and Geosciences

JF - Computers and Geosciences

IS - 2

ER -

Zonation of sequences of heteroscedastic multivariate data

Abstract

Keywords

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