搜索结果: 1-9 共查到“理学 Principal components”相关记录9条 . 查询时间(0.046 秒)
Prediction by Supervised Principal Components
Gene expression Microarray Regression Survival analysis
2015/8/21
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
Canonical correlation analysis DNA copy number Integrative genomic analysis L1 Matrix decomposition Principal component analysis Sparse principal component analysis SVD.
2015/8/21
We present a penalized matrix decomposition (PMD), a new framework for computing a rank-K approximation for a matrix. We approximate the matrix X as X ˆ = k K=1 dkukvk T , where dk, uk, and vk m...
Principal components analysis (PCA) is a classical method for the reduction of dimensionality of
data in the form of n observations (or cases) of a vector with p variables. Contemporary data sets
of...
ON THE DISTRIBUTION OF THE LARGEST EIGENVALUE IN PRINCIPAL COMPONENTS ANALYSIS
LARGEST EIGENVALUE PRINCIPAL COMPONENTS
2015/8/20
Let x1 denote the square of the largest singular value of an n × p
matrix X, all of whose entries are independent standard Gaussian varates. Equivalently, x1 is the largest principal component vari...
A Monte Carlo comparison between ridge and principal components regression methods
Multicollinearity ridge regression principal component regression
2010/9/15
A basic assumption concerned with general linear regression model is that there is no correlation (or no multicollinearity) between the explanatory variables. When this assumption is not satisfied, th...
Factors influencing fluffy layer suspended matter (FLSM) properties in the Odra River - Pomeranian Bay - Arkona Deep System (Baltic Sea) as derived by principal components analysis (PCA), and cluster analysis (CA)
fluffy layer suspended matter Odra River Arkona Deep System principal components analysis cluster analysis
2009/5/18
Factors conditioning formation and properties of suspended matter resting on the sea floor (Fluffy Layer Suspended Matter - FLSM) in the Odra river mouth - Arkona Deep system (southern Baltic Sea) wer...
Spatio-temporal variability and principal components of the particle number size distribution in an urban atmosphere
Spatio-temporal variability particle number size distribution urban atmosphere
2009/5/15
A correct description of fine (diameter <1 μm) and ultrafine (<0.1 μm) aerosol particles in urban areas is of interest for particle exposure assessment but also basic atmospheric research. We examined...
ASYMPTOTIC THEORIES FOR THE ROBUST PP ESTIMATORS OF THE PRINCIPAL COMPONENTS AND DISPERSION MATRIX Ⅲ.BOOTSTRAP CONFIDENCE SETS,BOOTSTRAP TESTS
Bootstrap confidence sets eigenvalues an
2007/8/7
In this paper the bootstrap theories, which are based on the author's former paper, of M-typ eprincipal components and dispersion matrices and M-type PP tests for multivariate locationand scale are ob...