This book is carefully written to give a good balance between theory and application of various missing data estimation techniques.
– Tshilidzi Marwala, University of Witwatersrand, South Africa
An opening discussion of traditional missing data issues is followed by chapters covering a range of computational intelligence.
– Book News Inc. (June 2009)
Paradoxically, in these days of information glut, there is a concurrent problem of data loss--missing and incomplete data. Statisticians have generated a wealth of knowledge on the methods of handling missing data. While solving differential equations, it is common to encounter such problems as missing initial conditions, missing boundary conditions, and unspecified location of the boundary contour. Such inverse problems, said to be improperly posed, are often solved by regularization--a method of systematically guessing the missing values. [...] A decent attempt at assembling the available tools under one cover.
– Rao Vemur, Computing Reviews