کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1181540 | 962955 | 2011 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Least-squares approximation of a space distribution for a given covariance and latent sub-space
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, a new method to approximate a data set by another data set with constrained covariance matrix is proposed. The method is termed Approximation of a DIstribution for a given COVariance (ADICOV). The approximation is solved in any projection subspace, including that of Principal Component Analysis (PCA) and Partial Least Squares (PLS). Given the direct relationship between covariance matrices and projection models, ADICOV is useful to test whether a data set satisfies the covariance structure in a projection model. This idea is broadly applicable in chemometrics. Also, ADICOV can be used to simulate data with a specific covariance structure and data distribution. Some applications are illustrated in an industrial case of study.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 105, Issue 2, 15 February 2011, Pages 171–180
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 105, Issue 2, 15 February 2011, Pages 171–180
نویسندگان
José Camacho, Pablo Padilla, Jesús Díaz-Verdejo, Keith Smith, David Lovett,