Optimum exponential regression with one nonlinear term

Kuldeep Kumar

doi:10.1016/0096-3003(92)90011-O

Optimum exponential regression with one nonlinear term

Kuldeep Kumar^*

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

A method is suggested for estimating regression parameters for a model E(Y = a + bX + ce^-∂t, where observations on Y, X and t are given. This model has been extensively used in economics for relating optimum output of a production process with the available labor and services. This method is optimum in the sense it involves minimizing the error sum of squares for the linear regression of Y on X and e^-∂t over the range ∂>0. The limits as ∂ → 0 and ∂ → ∞ are obtained and the computational procedure is discussed.

Original language	English
Pages (from-to)	51-58
Number of pages	8
Journal	Applied Mathematics and Computation
Volume	50
Issue number	1
DOIs	https://doi.org/10.1016/0096-3003(92)90011-O
Publication status	Published - Jul 1992
Externally published	Yes

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title = "Optimum exponential regression with one nonlinear term",

abstract = "A method is suggested for estimating regression parameters for a model E(Y = a + bX + ce-∂t, where observations on Y, X and t are given. This model has been extensively used in economics for relating optimum output of a production process with the available labor and services. This method is optimum in the sense it involves minimizing the error sum of squares for the linear regression of Y on X and e-∂t over the range ∂>0. The limits as ∂ → 0 and ∂ → ∞ are obtained and the computational procedure is discussed.",

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AB - A method is suggested for estimating regression parameters for a model E(Y = a + bX + ce-∂t, where observations on Y, X and t are given. This model has been extensively used in economics for relating optimum output of a production process with the available labor and services. This method is optimum in the sense it involves minimizing the error sum of squares for the linear regression of Y on X and e-∂t over the range ∂>0. The limits as ∂ → 0 and ∂ → ∞ are obtained and the computational procedure is discussed.

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DO - 10.1016/0096-3003(92)90011-O

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JO - Applied Mathematics and Computation

JF - Applied Mathematics and Computation

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ER -

Optimum exponential regression with one nonlinear term

Abstract

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