A MATLAB™ code to perform weighted linear regression with (correlated or uncorrelated) errors in bivariate data

Kaustubh Thirumalai; Arvind Singh; R. Ramesh

doi:10.1007/s12594-011-0044-1

A MATLAB^™ code to perform weighted linear regression with (correlated or uncorrelated) errors in bivariate data

Kaustubh Thirumalai
, Arvind Singh
, R. Ramesh

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

79 Scopus citations

Abstract

MATLAB^trade; is a powerful, easy to use, software package suitable for many mathematical operations, which finds plenty of scientific applications. One such application is the fitting of trend lines for a given data set so as to interpret the relationship of the variance of the parameters involved. We provide here a code in MATLAB^trade; that performs the weighted linear regression with (correlated or uncorrelated) errors in bivariate data which can handle 'force-fit' regression as well.

Original language	English (US)
Pages (from-to)	377-380
Number of pages	4
Journal	Journal of the Geological Society of India
Volume	77
Issue number	4
DOIs	https://doi.org/10.1007/s12594-011-0044-1
State	Published - Apr 2011
Externally published	Yes

Keywords

Bivariate regression
Correlated errors
Force fit
Trend line
Weighted linear regression

ASJC Scopus subject areas

Geology

Access to Document

10.1007/s12594-011-0044-1

Cite this

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title = "A MATLAB{\texttrademark} code to perform weighted linear regression with (correlated or uncorrelated) errors in bivariate data",

abstract = "MATLABtrade; is a powerful, easy to use, software package suitable for many mathematical operations, which finds plenty of scientific applications. One such application is the fitting of trend lines for a given data set so as to interpret the relationship of the variance of the parameters involved. We provide here a code in MATLABtrade; that performs the weighted linear regression with (correlated or uncorrelated) errors in bivariate data which can handle 'force-fit' regression as well.",

keywords = "Bivariate regression, Correlated errors, Force fit, Trend line, Weighted linear regression",

author = "Kaustubh Thirumalai and Arvind Singh and R. Ramesh",

note = "Funding Information: Acknowledgement: KT thanks the Indian Academy of Sciences for the fellowship provided to him for undertaking this work. We thank ISRO-GBP for funding.",

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T1 - A MATLAB™ code to perform weighted linear regression with (correlated or uncorrelated) errors in bivariate data

AU - Thirumalai, Kaustubh

AU - Singh, Arvind

AU - Ramesh, R.

N1 - Funding Information: Acknowledgement: KT thanks the Indian Academy of Sciences for the fellowship provided to him for undertaking this work. We thank ISRO-GBP for funding.

PY - 2011/4

Y1 - 2011/4

N2 - MATLABtrade; is a powerful, easy to use, software package suitable for many mathematical operations, which finds plenty of scientific applications. One such application is the fitting of trend lines for a given data set so as to interpret the relationship of the variance of the parameters involved. We provide here a code in MATLABtrade; that performs the weighted linear regression with (correlated or uncorrelated) errors in bivariate data which can handle 'force-fit' regression as well.

AB - MATLABtrade; is a powerful, easy to use, software package suitable for many mathematical operations, which finds plenty of scientific applications. One such application is the fitting of trend lines for a given data set so as to interpret the relationship of the variance of the parameters involved. We provide here a code in MATLABtrade; that performs the weighted linear regression with (correlated or uncorrelated) errors in bivariate data which can handle 'force-fit' regression as well.

KW - Bivariate regression

KW - Correlated errors

KW - Force fit

KW - Trend line

KW - Weighted linear regression

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