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- Missing and Modified Data in Nonparametric Estimation (With R Examples)
Missing and Modified Data in Nonparametric Estimation (With R Examples)
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Product Details
Author:
Sam Efromovich
Format:
Hardcover
Pages:
464
Publisher:
CRC Press (March 12, 2018)
Imprint:
Chapman and Hall/CRC
Language:
English
ISBN-13:
9781138054882
Weight:
36oz
Dimensions:
7" x 10"
File:
TAYLORFRANCIS-TayFran_261024042415025-20261024.xml
Folder:
TAYLORFRANCIS
List Price:
$166.99
Country of Origin:
United States
Pub Discount:
30
Series:
Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Case Pack:
14
As low as:
$158.64
Publisher Identifier:
P-CRC
Discount Code:
H
Overview
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.
