Comparison of Maximum Likelihood and Least Squares Cumulative Estimators for the Gompertz-Makeham Hazard Rate Function.
ARMY MATERIEL COMMAND TEXARKANA TEX INTERN TRAINING CENTER
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This research investigates the use of the cumulative distribution function and least squares analysis for estimating the three parameters of the hazard function, b ke sup-at. The least squares cumulative LSC estimators of the parameters are obtained by solving a system of nonlinear equations using the gradient method of Fletcher-Powell. The small sample property of the estimator is analyzed in a two-way comparison. Through Monte-Carle simulation, sample data sets with five to twenty-five time-to-failure data points are generated by assuming parameter values. The failure times are used as inputs to the LSC program and the resulting estimates are compared to maximum likelihood estimates.
- Statistics and Probability
- Manufacturing and Industrial Engineering and Control of Production Systems