Alan Polansky's Research

My research interests generally lie within the area of nonparametric statistics and industrial applications of statistics. My latest research is centered around observed confidence levels, which are a neat way to avoid multiple comparisons in multiple testing problems. A list of my publications sorted according to subject matter is provided below. Please note that due to the increasingly stringent rules regarding copyrights, I am unable to provide either preprints or off-prints online. Please contact me directly.

Observed Confidence Levels:

Polansky, A. M. (2007). Observed Confidence Levels: Theory and Application. CRC/Chapman and Hall.

Polansky, A. M. (2003). Supplier selection based on bootstrap confidence regions of process capability indices. Reliability, Quality and Safety Engineering, 10, 114. 18. 

Polansky, A. M. (2003). Selecting the best treatment in designed experiments. Statistics in Medicine, 22, 34613471.

 

Resampling Papers:

Guerra, R., Polansky, A. M. and Schucany, W. R. (1997). Smoothed bootstrap confidence intervals with discrete data. Computational Statistics and Data Analysis, 26, 163-176.

Polansky, A. M. (1997). Inexact control variates for the iterated bootstrap. Journal of Statistical Computation and Simulation, 59, 83-99.

Polansky, A. M. (1999). Upper bounds on the true coverage of bootstrap percentile type confidence intervals. American Statistician, 53, 362-369.

Polansky, A. M. (2000). Stabilizing bootstrap-t confidence intervals for small samples. Canadian Journal of Statistics, 28, 501-516.

Polansky, A. M. (2000). Bandwidth selection for the smoothed bootstrap percentile method. Computational Statistics and Data Analysis, 36, 333-349..

Polansky, A. M. (2003). Selecting the best treatment in designed experiments. Statistics in Medicine, 22, 3461-3471.

Polansky, A. M. (2007). Detecting change-points in Markov chains. Computational Statistics and Data Analysis, to appear.

Polansky, A. M. (2007). Sampling from virtual populations. Encyclopedia of Statistics in Quality and Reliability, to appear.

Polansky, A. M. and Check, C. E. (2001). Test for trends in environmental compliance. Journal of Agricultural, Biological and Environmental Statistics, 7, 452-468.

Polansky, A. M. and Schucany, W. R. (1997). Kernel smoothing to improve bootstrap confidence intervals. Journal of the Royal Statistical Society, Series B, 59, pp. 821-838.

 

Smoothing Papers:

Polansky, A. M. and Baker E. R. (2000). Multistage plug-in bandwidth selection for kernel distribution function estimates. Journal of Statistical Computation and Simulation, 65, 63-80.

Polansky, A. M. (2005). Nonparametric estimation of distribution functions of non-standard mixtures. Communications in Statistics - Theory and Methods, 34, 17111724.

 

Quality Control Papers:

Chou, Y.-M. and Polansky, A. M. (1993). Power of tests of some process capability indices. Communications in Statistics, Series B: Simulation and Computation, 22, pp. 523-544.

Chou, Y.-M. and Polansky, A. M. (1996). Fitting SPC data using a sample quantile ratio. ASA Proceedings of the Section on Quality and Productivity, 9-16. American Statistical Association, Alexandria, Virginia. 

Chou, Y.-M., Polansky, A. M., and Mason, R. L. (1998). Transforming non-normal data to normality in statistical process control. Journal of Quality Technology, 30, 133-141.

Chou, Y.-M. and Polansky, A. M. (2007). Process capability indices for non-normal distributions. Encyclopedia of Statistics in Quality and Reliability, to appear.

Polansky, A. M. (1998). A smooth nonparametric approach to process capability. Quality and Reliability Engineering International, 14, 43-48.

Polansky, A. M. (2000). An algorithm for computing a smooth nonparametric process capability estimate. Journal of Quality Technology, 32, 284-289.

Polansky, A. M. (2000). A smooth nonparametric approach to multivariate process capability. Technometrics, 43, 199-211.

Polansky, A. M. (2003). Supplier selection based on bootstrap confidence regions of process capability indices. Reliability, Quality and Safety Engineering, 10, 1-14.

Polansky, A.M. (2004). A general framework for constructing control charts. To appear in Quality and Reliability Engineering International. 

Polansky, A. M., Chou, Y.-M., and Mason, R. L. (1999). An algorithm for fitting Johnson transformations to non-normal data. Journal of Quality Technology, 31, 345-350.

Polansky, A. M., Chou, Y.-M. and Mason R. L. (1998). Estimating process capability indices for truncated distributions. Quality Engineering, 11, 257-265.

Polansky, A. M. and Kirmani, S. N. U. A. (2002). Quantifying the capability of industrial processes. Handbook of Statistics: Statistics in Industry, Volume 22, 625-656. 

Polansky, A. M. (2006). Permutation methods for comparing process capabilities. Journal of Quality Technology, 38, 254266.

Polansky, A. M. (2005). A general framework for constructing control charts. Quality and Reliability Engineering International, 21, 633653.

Polansky, A. M. (2007). Nonparametric process capability indices. Encyclopedia of Statistics in Quality and Reliability, to appear.

Consulting Publications

Fischer, M. P. and Polansky A. M. (2006). Influence of flaws in joint spacing and saturation: Results of one-dimensional mechanical modeling. Journal of Geophysical Research, 111, B07403.


This page is maintained by Alan M. Polansky. The views and opinions expressed on these pages are those of the author and do not necessarily reflect those of Northern Illinois University or the State of Illinois. 

This page was last updated on Thursday, January 24, 2008 08:13:24 AM


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