Please use this identifier to cite or link to this item: https://doi.org/10.1061/40803(187)107
Title: Bootstrap estimation of sample autocorrelation functions
Authors: Phoon, K.-K. 
Issue Date: 2006
Source: Phoon, K.-K. (2006). Bootstrap estimation of sample autocorrelation functions. GeoCongress 2006: Geotechnical Engineering in the Information Technology Age 2006 : 107-. ScholarBank@NUS Repository. https://doi.org/10.1061/40803(187)107
Abstract: It is rarely appreciated that the sample autocorrelation function is a non-stationary stochastic process with mean and variance that are functions of the lag distance. For Gaussian processes, some complex formulae for the mean and covariance of the sample autocorrelation function are available. Analytical solutions for non-Gaussian processes are probably intractable and none seems to be available. A more hopeful strategy is to exploit growing desktop computational power and increasingly powerful simulation techniques for stochastic processes to perform bootstrapping. Numerical results presented in this study show that fairly accurate mean estimates of the sample autocorrelation function can be obtained for both Gaussian and non-Gaussian processes using bootstrapping. Variance estimates are less accurate, but even crude estimates are useful in identifying the level of noise at large lags and reducing misinterpretation of how the actual autocorrelation function decays with lag distance. Copyright ASCE 2006.
Source Title: GeoCongress 2006: Geotechnical Engineering in the Information Technology Age
URI: http://scholarbank.nus.edu.sg/handle/10635/74086
ISBN: 0784408033
DOI: 10.1061/40803(187)107
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