## Abstract

Many practical applications of learning theory in the aircraft industry require the estimation of the parameters of y_{i} = αiβ where y_{t} is the cost of the i^{th} aircraft. Typically data are available by production lot rather than by individual aircraft. The estimation procedure usually employed is the application of least squares to log y_{v} = log α = β log x_{v} where y_{v} is the mean cost of a production lot and x_{v} is a quantity “near” the mean of serial numbers of the craft. This note presents a probability model which leads directly to maximum likelihood estimators and avoids difficulties inherent in the usual approach. An example of estimation employing methods of non-linear estimation is presented.

Original language | English (US) |
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Pages (from-to) | 1247-1252 |

Number of pages | 6 |

Journal | Journal of the American Statistical Association |

Volume | 63 |

Issue number | 324 |

DOIs | |

State | Published - Dec 1968 |

## All Science Journal Classification (ASJC) codes

- Statistics and Probability
- Statistics, Probability and Uncertainty