ABSTRACT

In this book, data partitioning refers to procedures where some observations from the sample are removed as part of the analysis. These techniques are used for the following purposes:

• To evaluate the accuracy of the model or classification scheme;

• To decide what is a reasonable model for the data; • To find a smoothing parameter in density estimation;

• To estimate the bias and error in parameter estimation; • And many others.