A unified approach to multiple‐set canonical correlation analysis and principal components analysis

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

doi:10.1111/j.2044-8317.2012.02052.x

Cited by 23 publications

(21 citation statements)

References 29 publications

(38 reference statements)

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“…Representation constrained canonical correlation analysis (Mishra, 2009) (Mishra, 2009;Hwang et al, 2013;Choi et al, 2017).…”

Section: Canonical Correlation Of Democracy and Globalizationmentioning

confidence: 99%

Are Democratic Regimes Antithetical to Globalization?

Mishra

2017

SSRN Journal

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In this study we have made an attempt to investigate into the relationship between political regime type (that ranges from authoritarian to democratic) and the extent of globalization, which of late has been considered as a path to development. We have made use of the Democracy index (and its constituent indicators) provided by the Economist Intelligence Unit and the globalization index (and its constituent indicators) of the KOF. Applying canonical correlation analysis on the data we have made an attempt to look into the response of globalization to the quantitative measures of democratic (versus authoritarian) practices of the governments in 116 countries distributed over Asia, Africa, Australia/Oceania, Europe and the Americas. We have also tested the Lee thesis in the context of globalization as a path to development. Our findings indicate that the empirical support to Lee's thesis if extended to globalization as a path to development is superficial and does not withstand critical analysis. Contrary to Lee's thesis, democracy promotes globalization. In African countries political discordance (at the national as well as international level) is not much favourable while in the Asian countries, political will, irrespective of regime type, is more or less in concordance with globalization. Therefore, rather illusively, it so appears that democracies thwart development as well as globalization as a means to development by implication, while the reality is very different.

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“…Representation constrained canonical correlation analysis (Mishra, 2009) (Mishra, 2009;Hwang et al, 2013;Choi et al, 2017).…”

Section: Canonical Correlation Of Democracy and Globalizationmentioning

confidence: 99%

Are Democratic Regimes Antithetical to Globalization?

Mishra

2017

SSRN Journal

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“…The robust determination of the covariance matrix and the associated mean values is essential to the successful application of this modern technique [26]. In the current study, CCA was performed on the many quantitative parameters taken from the CFs and BFs to abstract the main parameters pair of the typical variable and correlation coefficient.…”

Section: Canonical Correlation Analysis (Cca)mentioning

confidence: 99%

A quality evaluation strategy for Rhizoma coptidis from a variety of different sources using chromatographic fingerprinting combined with biological fingerprinting

Yan

Xiong

et al. 2013

Chin. Sci. Bull.

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Most of herbal medicines of different sources are used for the same treatment goal in clinic despite their tremendous differences of the quality. Because the clinical efficacy is closely related to the quality of medicines, the implementation of an effective quality control (QC) process is vital. Chemical methods based on content determination and chromatographic fingerprints (CFs) have been recommended as powerful tools. In spite of advances in QC, it is still difficult to determine that which of the chemical compositions can best reflect the correlation with the desired biological activity. Herein, we have focused on the biological activities of multi-source herbal medicines to establish an analytical method. By looking for correlations between the biological activities and their chemical compositions, the method can identify reasonable chemical indicators or chemical methods with biological activity information. In this study, high-performance liquid chromatography (HPLC) and microcalorimetry are combined as a useful method for evaluating the quality of Rhizoma coptidis from different sources. The results of biological fingerprints (BFs) showed that the antibacterial activity sequence of R. coptidis of different sources was Coptis teeta Wall. (CT)>Coptis chinensis Franch. (CC)>Coptis deltoidea C.Y. Cheng et Hsiao (CD). The "spectrum-activity" relationships between CFs and BFs were investigated using the canonical correlation analysis (CCA). Compared with the CCA result of CFs and BFs, the canonical correlation coefficient r 1 and r 2 were 0.9974 and 0.9752, respectively. It revealed that there are a close correlation between the spectrum-activity relationships and several of the major anti-bacterial components in the CFs, including jatrorrhizine, coptisine, palmatine, and berberine. Of course, R. coptidis was only a representative of multisource medical plants. The result of the current study will provide an effective reference for evaluating the quality of multisource herbal medicines.Rhizoma coptidis, multi-source medical plants, quality control, chromatographic fingerprint, biological fingerprint Citation:Li J X, Yan D, Ma L N, et al. A quality evaluation strategy for Rhizoma coptidis from a variety of different sources using chromatographic fingerprinting combined with biological fingerprinting.

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“…Though not used in the context of medical imaging, there are methods that consider these two problems jointly, see e.g. , [17, 40], however these techniques are heuristic and will fail in the sample-poor regime [30]. …”

Section: Introductionmentioning

confidence: 99%

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data

et al. 2016

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Due to their data-driven nature, multivariate methods such as canonical correlation analysis (CCA) have proven very useful for fusion of multimodal neurological data. However, being able to determine the degree of similarity between datasets and appropriate order selection are crucial to the success of such techniques. The standard methods for calculating the order of multimodal data focus only on sources with the greatest individual energy and ignore relations across datasets. Additionally, these techniques as well as the most widely-used methods for determining the degree of similarity between datasets assume sufficient sample support and are not effective in the sample-poor regime. In this paper, we propose to jointly estimate the degree of similarity between datasets and their order when few samples are present using principal component analysis and canonical correlation analysis (PCA-CCA). By considering these two problems simultaneously, we are able to minimize the assumptions placed on the data and achieve superior performance in the sample-poor regime compared to traditional techniques. We apply PCA-CCA to the pairwise combinations of functional magnetic resonance imaging (fMRI), structural magnetic resonance imaging (sMRI), and electroencephalogram (EEG) data drawn from patients with schizophrenia and healthy controls while performing an auditory oddball task. The PCA-CCA results indicate that the fMRI and sMRI datasets are the most similar, whereas the sMRI and EEG datasets share the least similarity. We also demonstrate that the degree of similarity obtained by PCA-CCA is highly predictive of the degree of significance found for components generated using CCA.

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A unified approach to multiple‐set canonical correlation analysis and principal components analysis

Cited by 23 publications

References 29 publications

Are Democratic Regimes Antithetical to Globalization?

Are Democratic Regimes Antithetical to Globalization?

A quality evaluation strategy for Rhizoma coptidis from a variety of different sources using chromatographic fingerprinting combined with biological fingerprinting

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data

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