Patterns of Cortical Structures and Cognition in Antipsychotic-Naïve Patients With First-Episode Schizophrenia: A Partial Least Squares Correlation Analysis

2019 ◽  
Vol 4 (5) ◽  
pp. 444-453 ◽  
Author(s):  
Kasper Jessen ◽  
Rene C.W. Mandl ◽  
Birgitte Fagerlund ◽  
Kirsten B. Bojesen ◽  
Jayachandra M. Raghava ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
First Episode ◽  
First Episode Schizophrenia

Creativity as a Tool of Tourism Development

2020 ◽  
pp. 504-530
Author(s):  
Alžbeta Kiráľová
Keyword(s):  
Czech Republic ◽  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Tourism Development ◽  
Multivariate Methods ◽  
The Czech Republic ◽  
Future Studies

This chapter shows how creativity is bounded with tourism development in the destination. It points out the influence of changes in visitors´ behavior on the destinations, defines creativity, and discusses the relation of culture and creativity in tourism. The chapter focuses on the relation between creativity and development of tourism in the Czech Republic´s regions in the pre-crisis, crisis and after-crisis period. The destinations were subjects to research using two multivariate methods i.e. canonical correlation analysis (CCA) and partial least squares (PLS). The chapter also makes suggestions for future studies.

Other Tensor Analysis and Further Direction

2011 ◽  
pp. 226-252
Author(s):  
David Zhang ◽  
Fengxi Song ◽  
Yong Xu ◽  
Zhizhen Liang
Keyword(s):  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Tensor Analysis ◽  
Tensor Methods

In this chapter, we describe tensor-based classifiers, tensor canonical correlation analysis and tensor partial least squares, which can be used in biometrics. Section 11.1 gives background and devolvement of these tensor methods. Section 11.2 introduces tensor-based classifiers. Section 11.3 gives tensor canonical correlation analysis and tensor partial least squares. We summarize this chapter in Section 11.4.

Creativity as a Tool of Tourism Development

2017 ◽  
pp. 67-93
Author(s):  
Alžbeta Kiráľová
Keyword(s):  
Czech Republic ◽  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Tourism Development ◽  
Multivariate Methods ◽  
The Czech Republic ◽  
Future Studies

This chapter shows how creativity is bounded with tourism development in the destination. It points out the influence of changes in visitors´ behavior on the destinations, defines creativity, and discusses the relation of culture and creativity in tourism. The chapter focuses on the relation between creativity and development of tourism in the Czech Republic´s regions in the pre-crisis, crisis and after-crisis period. The destinations were subjects to research using two multivariate methods i.e. canonical correlation analysis (CCA) and partial least squares (PLS). The chapter also makes suggestions for future studies.

scholarly journals Corticomuscular Activity Modeling by Combining Partial Least Squares and Canonical Correlation Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xun Chen ◽  
Aiping Liu ◽  
Z. Jane Wang ◽  
Hu Peng
Keyword(s):  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Medical Knowledge ◽  
Data Sets ◽  
Data Set ◽  
Activity Modeling ◽  
Multiple Data Sets

Corticomuscular activity modeling based on multiple data sets such as electroencephalography (EEG) and electromyography (EMG) signals provides a useful tool for understanding human motor control systems. In this paper, we propose modeling corticomuscular activity by combining partial least squares (PLS) and canonical correlation analysis (CCA). The proposed method takes advantage of both PLS and CCA to ensure that the extracted components are maximally correlated across two data sets and meanwhile can well explain the information within each data set. This complementary combination generalizes the statistical assumptions beyond both PLS and CCA methods. Simulations were performed to illustrate the performance of the proposed method. We also applied the proposed method to concurrent EEG and EMG data collected in a Parkinson’s disease (PD) study. The results reveal several highly correlated temporal patterns between EEG and EMG signals and indicate meaningful corresponding spatial activation patterns. In PD subjects, enhanced connections between occipital region and other regions are noted, which is consistent with previous medical knowledge. The proposed framework is a promising technique for performing multisubject and bimodal data analysis.

Comparison of variants of canonical correlation analysis and partial least squares for combined analysis of MRI and genetic data

NeuroImage ◽  
2015 ◽  
Vol 107 ◽  
pp. 289-310 ◽  
Author(s):  
Claudia Grellmann ◽  
Sebastian Bitzer ◽  
Jane Neumann ◽  
Lars T. Westlye ◽  
Ole A. Andreassen ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Genetic Data ◽  
Combined Analysis
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