Many practical applications of learning theory in the aircraft industry require the estimation of the parameters of yi = αiβ where yt is the cost of the ith 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 yv = log α = β log xv where yv is the mean cost of a production lot and xv 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.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty