• No results found

Rotation of principal components

Comparing G Matrices: Are Common Principal Components Informative?

Comparing G Matrices: Are Common Principal Components Informative?

... nonorthogonal rotation is used, but such trans- regardless of the allele frequency in the other popula- formations do not result in modules in an evolutionary ...

16

Genetic mapping of principal components of canine pelvic morphology

Genetic mapping of principal components of canine pelvic morphology

... internal rotation of the innominate bone in pa- tients with DDH than in the control subjects along with increased acetabular anteversion angle and acetabular inclination ...Internal rotation of the ...

10

Direct Estimation of Genetic Principal Components

Direct Estimation of Genetic Principal Components

... successive principal component is conditioned on the PCs that have already been esti- ...the principal components (Juga and Thompson 1992; Pinheiro and Bates ...A rotation is defined by an ...

12

High Dimensional Dataset Compression Using  Principal Components

High Dimensional Dataset Compression Using Principal Components

... The rotation algorithm used in this ana- lysis is Varimax ...“orthogonal” rotation, indicating the transformation matrix (T) in (3) is orthogonal as TT T = ...

11

The ‘not-so-strange’ body in the mirror: A principal components analysis of direct and mirror self-observation : A principal components analysis of direct and mirror self-observation

The ‘not-so-strange’ body in the mirror: A principal components analysis of direct and mirror self-observation : A principal components analysis of direct and mirror self-observation

... above. Principal Components Analyses (PCA) with varimax rotation was then used to investigate the structure underlying direct and mirror self-observation of the body, using scores from the ...

61

Principal Components Analysis a method Useful in Identification of Clusters of Variables

Principal Components Analysis a method Useful in Identification of Clusters of Variables

... of components extracted during principal components analysis was equal to the number of variables that were put into ...18 components. The sum of variance accounted by these components ...

6

Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation

Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation

... Principal components analysis (PCA) is a well-known statis- tical technique that has been widely applied to solve impor- tant signal processing problems like feature extraction, sig- nal estimation, ...

8

Principal Components Analysis with Spline Optimal Transformations for Continuous Data

Principal Components Analysis with Spline Optimal Transformations for Continuous Data

... An early attempt to generalize PCA was made by Gnanadesikan and Wilk in the ‘60’s. The idea was to extend the m-dimensional space by adding nonlinear functions of the original variables (quadratic and higher order terms) ...

9

Application of Principal Components Analysis Results in Visual Network Analysis

Application of Principal Components Analysis Results in Visual Network Analysis

... of principal components analysis application in economic and financial tasks demonstrates its efficiency in playing the role of a preprocessor in the process of network visual analysis (graphs, social ...

9

Principal Components based Spectrum Sensing Algorithms for Cognitive Radio

Principal Components based Spectrum Sensing Algorithms for Cognitive Radio

... Xin Wang et al [2] described to spectrum sensing based on dimensionality reduction and random forest (RF) in low signal-to-noise ratio environments. Classifications of three digital modulation types, including BPSK, OFDM ...

5

Discriminant analysis under the common principal components model

Discriminant analysis under the common principal components model

... Abstract: For two or more populations of which the covariance matrices have a com- mon set of eigenvectors, but different sets of eigenvalues, the common principal com- ponents (CPC) model is appropriate. Pepler ...

26

Study of transportation-and-storage system using the method of principal components

Study of transportation-and-storage system using the method of principal components

... Експертним шляхом були виділені 14 параметрів, які, зазвичай, використовуються для моделювання якісних показників в транспортних процесах: – загальна кількість вагонів, що надходять на к[r] ...

9

Linkage analysis using principal components of gene expression data

Linkage analysis using principal components of gene expression data

... The principal components results represent values at the same relative region as those found using the two other methods (single probe, Morley et ...the principal component that was used to find the ...

5

Spectrum sensing using low complexity principal components for cognitive radios

Spectrum sensing using low complexity principal components for cognitive radios

... Cognitive radio has the ability to communicate over the unused frequency spectrum intelligently and adaptively. Spectrum sensing in a cognitive radio (CR) is crucial in generating awareness about the radio environment ...

8

Taxonomical analysis of regional development by outranking relations on multiple principal components

Taxonomical analysis of regional development by outranking relations on multiple principal components

... With the recent emergence of interest in and need for regional planning, especially in under-developed economies, economists experienced uneasiness with regard to all the three norms mentioned above, and hence, there is ...

7

Nonlinear Regression Estimation Using Subset-Based Kernel Principal Components

Nonlinear Regression Estimation Using Subset-Based Kernel Principal Components

... Kernel Principal Components Analysis (KPCA) for the random covariate X ...linear Principal Component Analysis (PCA) and overcomes the limitations of the linear PCA by conducting the ...

36

Analysis of Principal Components of the Sea Ice Concentration Fields in the Barents Sea

Analysis of Principal Components of the Sea Ice Concentration Fields in the Barents Sea

... the principal components of the sea ice concentration fields in the Barents Sea make it possible to distinguish three modes of inter- annual variability of the sea ice ...

8

Amendments of a Stochastic Restricted Principal Components Regression Estimator in the Linear Model

Amendments of a Stochastic Restricted Principal Components Regression Estimator in the Linear Model

... restricted principal components (SRPC) regression estimator ignoring the number of components (orthogonal matrix I J ) that has been chosen to solve the multicollinearity problem in the data matrix ...

9

A principal components analysis of the UK term structure and the influence of fiscal policy

A principal components analysis of the UK term structure and the influence of fiscal policy

... Dynamic Equation for Inflation Dynamic Equation for the Change in the Deviation of GDP frorn its Trend Dynamic Equation for the Change in Interest Paymentsas a Ratio of Total Gilts Outst[r] ...

362

Correctness results for on-line robust principal components analysis

Correctness results for on-line robust principal components analysis

... Principal Components Analysis (PCA) is a tool that is frequently used for dimension reduc- ...called principal components, that contain most of the variability of the ...called ...

170

Show all 6601 documents...

Related subjects