Kontakt
Kako kupovati
Dostava
Savjetnik za kupnju
Engleski
125 b
30 dana za povrat kupljenih proizvoda
Kupci su kupili i
Partial least squares (PLS) has become an important statistical tool for modeling relations between sets of observed variables by means of latent variables especially for statistical problems dealing with high dimensional data sets. Despite of the fact that PLS handles multicollinearity problem, it fails to deal with data containing outliers since it is based on maximizing the sample covariance matrix between the response(s) and a set of explanatory variables, which is known to be sensitive to outliers. Existence of multicollinearity and outliers is no exception in real data sets, and it leads to a requirement of robust PLS methods in several application areas such as chemometrics. This book provides a detailed literature review on classical and robust PLS methods. The book introduces two new robust PLS methods that can be applied to regression (RoPLS) and classification (RoCPLS) problems. The content of the book should be especially useful for graduate students in statistics as a complementary material for classical multivariate data analysis courses and other researchers who can adopt the provided methodologies for real data analysis.
Informacije o knjizi
Engleski
Kategorija
Poklonite ovu knjigu još danas
To je jednostavno
1 Dodajte knjigu u košaricu i odaberite isporuku kao poklon 2 Zauzvrat ćemo vam poslati kupon 3 Knjiga dolazi na adresu poklonoprimcaMoglo bi vas zanimati i
/
Tvrdi uvez
50.63
€
/
Meki uvez
37.36
€
/
Meki uvez
14.27
€
/
Meki uvez
14.47
€
/
Tvrdi uvez
385.68
€
Dobar dan! Ja sam Libroamiko, vaš književni savjetnik.
Kako vam mogu pomoći?