AN INTRODUCTION TO S-SMART
Another Look at the Bootstrap
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Resampling as a revolutionary methodology to deal with small-sample problems has been developed rapidly with the growth of modern computer techniques. This book introduces a new resampling method, the sample smoothing amplification resampling technique (S-SMART) which can produce amplified samples with adequate statistical power, conditional independence of observations, robustness to outliers, stable statistical behaviors, and an identical distribution with its small random proto-sample from any distributions. An empirical example is also provided as guidance for readers to apply S-SMART to t...
Resampling as a revolutionary methodology to deal with small-sample problems has been developed rapidly with the growth of modern computer techniques. This book introduces a new resampling method, the sample smoothing amplification resampling technique (S-SMART) which can produce amplified samples with adequate statistical power, conditional independence of observations, robustness to outliers, stable statistical behaviors, and an identical distribution with its small random proto-sample from any distributions. An empirical example is also provided as guidance for readers to apply S-SMART to their own research using small samples. This book also includes a systematic overview and comparison of other major resampling methods, including the Bootstrap; therefore, applied statisticians and quantitative researchers not only can use the book as an introduction to S-SMART, but also can consult it for information about other resampling methods.
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