Smoothing the global mean based on functional principal component analysis
Küçük Resim Yok
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Maltepe Üniversitesi
Erişim Hakkı
CC0 1.0 Universal
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Özet
There are many cases in almost all application fields where the estimation of population parameters is carried out using sparse data. The data may be time or space ( r) dependent. When such data comes from a set of n trajectories (subjects), the Functional Principal Component Analysis (FPCA) is used to process the data for estimation purposes. In this study, the estimation and smoothing of global mean is considered.
Açıklama
Anahtar Kelimeler
Smoothing, Functional, Sparse data, Covariance
Kaynak
International Conference of Mathematical Sciences
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Tandoğdu, Y. ve Cidar, Ö. (2009). Smoothing the global mean based on functional principal component analysis. Maltepe Üniversitesi. s. 394.
