Bias/Variance Trade-Off in Estimates of a Process Parameter Based on Temporal Data

• Autores: Patricia L. Cooper Barfoot, Stefan H. Steiner, R. Jock Mackay Mackay
• Localización: Journal of quality technology: A quarterly journal of methods applications and related topics, ISSN 0022-4065, Vol. 49, Nº. 4, 2017, págs. 301-319
• Idioma: inglés
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• Resumen

  • We recommend an approach to estimate a process performance measure (or parameter) at the present time from a stream of data where the performance may drift slowly over time. It is common practice to estimate current process performance using either present-time data only or including all historical data. When sample sizes by time period are small, an estimate based only on present-time data is imprecise. When the performance changes over time, including historical data in estimation trades more bias for less variability. We propose to regulate the bias/variance trade-off using estimating equations that down-weight past data. We derive approximations for the variance of the estimator and the distribution of a test statistic involving the estimator. The work is motivated by estimation of a customer loyalty measure where realistic data demonstrates the proposed approach.