Statistical Methods for Handling Incomplete Data
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Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.
Features
- Now includes a chapter on Advanced Topics, including kernel ridge regression imputation and neural network model imputation
The book is primarily aimed at researchers and graduate students from statistics, and could be used as a reference by applied researchers with a good quantitative background. It includes many real data examples and simulated examples to help readers understand the methodologies.
Get Statistical Methods for Handling Incomplete Data by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Taylor & Francis Ltd and it has pages.
