### 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 |
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Pages (from-to) | 51-58 |

Number of pages | 8 |

Journal | Applied Mathematics and Computation |

Volume | 50 |

Issue number | 1 |

DOIs | |

Publication status | Published - Jul 1992 |

Externally published | Yes |

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*Applied Mathematics and Computation*, vol. 50, no. 1, pp. 51-58. https://doi.org/10.1016/0096-3003(92)90011-O

**Optimum exponential regression with one nonlinear term.** / Kumar, Kuldeep.

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

TY - JOUR

T1 - Optimum exponential regression with one nonlinear term

AU - Kumar, Kuldeep

PY - 1992/7

Y1 - 1992/7

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=38249012484&partnerID=8YFLogxK

U2 - 10.1016/0096-3003(92)90011-O

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

M3 - Article

VL - 50

SP - 51

EP - 58

JO - Applied Mathematics and Computation

JF - Applied Mathematics and Computation

SN - 0096-3003

IS - 1

ER -