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J.D. Opdyke's Blog (3)

Bootstraps, Permutation Tests, and Sampling Orders of Magnitude Faster Using SAS

Bootstraps, Permutation Tests, and Sampling Orders of Magnitude Faster Using SAS, Computational Statistics-WIREs, Vol. 5, Issue 5, 391-405.  Download @ http://www.datamineit.com/DMI_publications.htm

While permutation tests and bootstraps have very wide-ranging application, both share a common potential drawback: as data-intensive resampling methods, both can be runtime prohibitive when applied to large or even…

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Added by J.D. Opdyke on September 16, 2013 at 5:25am — No Comments

J.D. Opdyke, Author: A Powerful and Robust Nonparametric Statistic for Joint Mean-Variance Quality Control

For statistical process control, a number of single charts that jointly monitor both process mean and variability recently have been developed. For quality control-related hypothesis testing, however, there has been little analogous development of joint mean-variance tests: only one two-sample statistic that is not computationally intensive has been designed specifically for the one-sided test of Ho: Mean2<=Mean1 and StDev2<=StDev1 vs. Ha: Mean2>Mean1 OR StDev2>StDev1 (see…

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Added by J.D. Opdyke on March 9, 2012 at 5:42am — No Comments

Estimating Operational Risk Capital: the Challenges of Truncation, the Hazards of MLE, and the Promise of Robust Statistics

J.D. Opdyke and Alex Cavallo

In operational risk measurement, the estimation of severity distribution parameters is the main driver of capital estimates, yet this remains a non-trivial challenge for many reasons.  Maximum likelihood estimation (MLE) does not adequately meet this challenge because of its well-documented non-robustness to modest violations of idealized textbook model assumptions, specifically that the data are independent and identically distributed (i.i.d.), which is…

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Added by J.D. Opdyke on February 10, 2012 at 7:30pm — No Comments

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