Missing and Modified Data in Nonparametric Estimation : With R Examples
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The book gives a unified approach to nonparametric curve estimation based on missing and modified data. Missing data includes cases of missing at random and missing not at random, while data modification includes truncation and censoring, typical in survival analysis, as well as measurement errors and amplitude modulation. A universal nonparametric series E-estimator is used whose statistical idea is based on estimation of a population mean by a corresponding sample mean. While the approach is straightforward, the asymptotic theory shows that no other estimator can outperform the E-estimator.
Get Missing and Modified Data in Nonparametric Estimation by Jie Chen, Joseph Heyse 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 448 pages.
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