کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
415086 | 681168 | 2011 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An imputation method for categorical variables with application to nonlinear principal component analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: An imputation method for categorical variables with application to nonlinear principal component analysis An imputation method for categorical variables with application to nonlinear principal component analysis](/preview/png/415086.png)
چکیده انگلیسی
The problem of missing data in building multidimensional composite indicators is a delicate problem which is often underrated. An imputation method particularly suitable for categorical data is proposed. This method is discussed in detail in the framework of nonlinear principal component analysis and compared to other missing data treatments which are commonly used in this analysis. Its performance vs. these other methods is evaluated throughout a simulation procedure performed on both an artificial case, varying the experimental conditions, and a real case. The proposed procedure is implemented using R1.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 55, Issue 7, 1 July 2011, Pages 2410–2420
Journal: Computational Statistics & Data Analysis - Volume 55, Issue 7, 1 July 2011, Pages 2410–2420
نویسندگان
Pier Alda Ferrari, Paola Annoni, Alessandro Barbiero, Giancarlo Manzi,