Confidence Interval Estimation Using Standardized Time Series
Article Abstract:
Observations of a stationary stochastic process can be transformed into a standardized time series. Confidence interval estimation for the mean of a simulated time series is an active area of research. A major difficulty in obtaining confidence intervals from dependent stationary time series comes in estimating the value of this unknown standardized scalar parameter estimator. Instead of standardizing a single estimator, the techniques presented standardize the entire time series. The estimator is never calculated but the estimator is cancelled from the expressions used in confidence interval estimation. Tables show the performance of confidence interval estimators of various means.
Publication Name: Operations Research
Subject: Petroleum, energy and mining industries
ISSN: 0030-364X
Year: 1983
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Sequential Decision Making Under Uncertain Future Preferences
Article Abstract:
A model of sequential decision making under uncertain future preferences is presented. An optimal solution determined on the assumption that the initial preference is permanent may be rejected for a solution that offers more flexibility. The perceived utility function may change due to learning. In this model a description of preference, a vector of trade-off weights, changes from stage to stage.
Publication Name: Operations Research
Subject: Petroleum, energy and mining industries
ISSN: 0030-364X
Year: 1984
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