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Note---New Confidence Interval Estimators Using Standardized Time Series
Goldsman, David; Schruben, Lee - In: Management Science 36 (1990) 3, pp. 393-397
We develop new asymptotically valid confidence interval estimators (CIE's) for the underlying mean of a stationary simulation process. The new estimators are weighted generalizations of Schruben's standardized time series area CIE. We show that the weighted CIE's have the same asymptotic...
Persistent link: https://www.econbiz.de/10009214300
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Properties of Standardized Time Series Weighted Area Variance Estimators
Goldsman, David; Meketon, Marc; Schruben, Lee - In: Management Science 36 (1990) 5, pp. 602-612
We wish to estimate the variance of the sample mean from a continuous-time stationary stochastic process. This article expands on the results of a technical note (Goldsman and Schruben 1990) by using the theory of standardized time series to investigate weighted generalizations of Schruben's...
Persistent link: https://www.econbiz.de/10009218065
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Notes: Conditions for the Applicability of the Regenerative Method
Glynn, Peter W.; Iglehart, Donald L. - In: Management Science 39 (1993) 9, pp. 1108-1111
The regenerative method for estimating steady-state parameters is one of the basic methods in simulation output analysis. This method depends on central limit theorems for regenerative processes and weakly consistent estimates for the variance constants arising in the central limit theorems. A...
Persistent link: https://www.econbiz.de/10009214468
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Standardized Time Series Lp-Norm Variance Estimators for Simulations
Tokol, Gamze; Goldsman, David; Ockerman, Daniel H.; … - In: Management Science 44 (1998) 2, pp. 234-245
This paper studies a class of estimators for the variance parameter of a stationary stochastic process. The estimators are based on L<sub>p</sub> norms of standardized time series, and they generalize previously studied estimators due to Schruben. We show that the new estimators have some desirable...
Persistent link: https://www.econbiz.de/10009214570
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BAYESIAN FORECASTING USING STOCHASTIC SIMULATION
Muñoz Negrón, David F. - In: Journal of Economics, Finance and Administrative Science 14 (2009) 26, pp. 7-26
on the point forecast is assessed through the estimation of a conditional variance and a prediction interval. We discuss … how to construct asymptotic confidence intervals to assess the estimation error for the estimators obtained using …
Persistent link: https://www.econbiz.de/10009319482
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A Batch Means Methodology for Estimation of a Nonlinear Function of a Steady-State Mean
Muñoz, David F.; Glynn, Peter W. - In: Management Science 43 (1997) 8, pp. 1121-1135
We study the estimation of steady-state performance measures from an \frak{R}<sup>d</sup>-valued stochastic process Y … = {Y(t): t \ge 0} representing the output of a simulation. In many applications, we may be interested in the estimation of … more general problem---the estimation of a (nonlinear) function f(r) of r. We propose a batch-means-based methodology that …
Persistent link: https://www.econbiz.de/10009198064
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Folded overlapping variance estimators for simulation
Meterelliyoz, Melike; Alexopoulos, Christos; Goldsman, David - In: European Journal of Operational Research 220 (2012) 1, pp. 135-146
We propose and analyze a new class of estimators for the variance parameter of a steady-state simulation output process. The new estimators are computed by averaging individual estimators from “folded” standardized time series based on overlapping batches composed of consecutive...
Persistent link: https://www.econbiz.de/10011052497
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Optimal choice of k n -records in the extreme value index estimation
El Arrouchi, Mohamed; Imlahi, Abdelouahid - In: Statistics & Decisions 23 (2005) 2, pp. 101-115
Summary We propose an estimate for the index of extreme value distribution which based on k n -record values and show its consistency and asymptotic normality. The problem of specifying the optimal value of k  =  k n involved in our estimator is investigated. Some simulation results are also...
Persistent link: https://www.econbiz.de/10014621301
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Model selection and error estimation
Bartlett, P. L.; Boucheron, S.; Lugosi, G. - 2002
between error estimation and data-based complexity penalization: any good error estimate may be converted into a data …
Persistent link: https://www.econbiz.de/10009438376
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Equilibrium Tuition, Applications, Admissions and Enrollment in the College Market
Fu, Chao - 2010
equilibrium. I estimate the structural parameters of the model using the NLSY 97 data, via a three-step estimation procedure to …
Persistent link: https://www.econbiz.de/10009439060