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Permutation Inference for Canonical Correlation Analysis
[article]
2020
arXiv
pre-print
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Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements. ...
Even in the absence of nuisance variables, however, a simple permutation test for CCA also leads to excess error rates for all canonical correlations other than the first. ...
distribution, and inference is for the largest canonical correlation. ...
arXiv:2002.10046v4
fatcat:yyqgn34rrvh67he33itj5wjtcy
Permutation Inference for Canonical Correlation Analysis
2020
NeuroImage
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Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements. ...
Even in the absence of nuisance variables, however, a simple permutation test for CCA also leads to excess error rates for all canonical correlations other than the first. ...
Pine (National Institutes of Health, NIH) for the invaluable discussions. A.M.W. receives support through the NIH Intramural Research Program (ZIA-MH002781 and ZIA-MH002782). ...
doi:10.1016/j.neuroimage.2020.117065
pmid:32603857
pmcid:PMC7573815
fatcat:6wg2fxa5t5h67bochzmctwj7au
Canonical Correlation: Permutation Tests and Regression
2012
Communications for Statistical Applications and Methods
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In addition, we connect canonical correlation analysis to regression and we we show that certain inferences in regression can be done through canonical correlation analysis. ...
In this paper, we present a permutation test to select the number of pairs of canonical variates in canonical correlation analysis. ...
We show that certain inferences of regression analysis, for example ANOVA F-test, tests for heteroscedasticity, and reduced-rank regression, can be done via canonical correlation analysis. ...
doi:10.5351/ckss.2012.19.3.471
fatcat:evoknp5owvf6deit2p5zybt274
Statistical Inference in Canonical Correlation Analyses Exemplified by the Influence of North Atlantic SST on European Climate
2003
Journal of Climate
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Preisendorfer, 1987: Origins and levels of month- ly and seasonal forecast skill for United States surface air tem- peratures determined by canonical correlation analysis. Mon. Wea. ...
For each EOF truncation the significance level and the canonical correlation (100) are given for the first (Fig. 1, left) and the second (Fig. 1, right) canonical mode. ...
doi:10.1175/1520-0442(2003)016<0522:siicca>2.0.co;2
fatcat:gklznk5trvcn7bdlsh4muunvom
Page 533 of Journal of Climate Vol. 16, Issue 3
[page]
2003
Journal of Climate
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., except for one, all canonical correlations are zero). This is less probable in most cases where CCA is applied in climate research. ...
Conclusions
The article presents three parametric testing proce- dures in canonical correlation analysis (CCA): the Wilks, Hotelling—Lawley, and the Pillai—Bartlett test sta- tistics with respective approximations ...
Local White Matter Architecture Defines Functional Brain Dynamics
[article]
2018
arXiv
pre-print
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Second, by employing variable selection using sparse canonical correlation analysis and cross-validation, we show that segments of the local connectome are predictive of certain patterns of functional ...
First, by performing statistical inference on distance-based correlations, we show that similarity in the local connectome between individuals is significantly correlated with similarity in their patterns ...
For simplicity, we fix these constants to be 1 in our analysis. ...
arXiv:1804.08154v2
fatcat:dctqze4p2vd2bb4zk47ktudqxm
Evaluating Word Order Recursively over Permutation-Forests
2014
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation
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However, none of the existing metrics over permutations groups word positions recursively into larger phrase-like blocks, which makes it difficult to account for long-distance reordering phenomena. ...
We empirically compare PEFs metric against five known reordering metrics on WMT13 data for ten language pairs. ...
We also thank Ivan Titov for helpful comments on the ideas presented in this paper. ...
doi:10.3115/v1/w14-4017
dblp:conf/ssst/StanojevicS14
fatcat:h7tvurvgb5brlanr4kkq4dr24u
Sensory-modality independent activation of the brain network for language
2020
Journal of Neuroscience
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We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations ...
brain areas, both including and extending beyond the core network for language. ...
Multiset canonical correlation analysis. ...
doi:10.1523/jneurosci.2271-19.2020
pmid:32111697
pmcid:PMC7117900
fatcat:zrzw5e3genemdj4tlyosmmwkv4
Canonical correlation analysis: Assessing links between multiplex networks
2006
Social Networks
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A canonical correlation analysis (CCA) makes a particularly interesting example since it is the most general form of the general linear model. ...
Given the mechanics of the CCA and the method of permuting the data, the distributions of the canonical cross-loadings would generally be the most useful for inferring the relative contribution of each ...
The 95th percentile for each canonical correlation was used as the benchmark for evaluating the scree plot of the original canonical correlations (see Fig. 2 ). ...
doi:10.1016/j.socnet.2005.07.004
fatcat:rqzc7cs3bzfdtdshpt76ctnzga
A Tracy-Widom Empirical Estimator For Valid P-values With High-Dimensional Datasets
[article]
2018
arXiv
pre-print
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Classical multivariate approaches like Multivariate Analysis of Variance (MANOVA) and Canonical Correlation Analysis (CCA) can be used to study relationships between such multivariate datasets. ...
Through simulations, we show that this estimated distribution also leads to valid p-values that can be used for high-dimensional inference. ...
Analysis (PCA), Multivariate Analysis of Variance (MANOVA), Canonical Correlation Analysis (CCA), Principal Components of Explained Variance (PCEV), and Linear Discriminant Analysis (LDA); for a small ...
arXiv:1811.07356v1
fatcat:powqhlks5bejvcjikexkii247u
Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging
2015
Frontiers in Neuroscience
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One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). ...
To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. ...
We also thank Dr David Alsop for facilitating the 3D pseudo continuous ASL pulse sequence used in this work. ...
doi:10.3389/fnins.2015.00366
pmid:26528117
pmcid:PMC4603249
fatcat:rcjpfwma7nb2lkhll5xlp6khc4
Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data
2012
PLoS ONE
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A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. ...
Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly ...
Each gray line shows the computed canonical correlations for a single random permutation. ...
doi:10.1371/journal.pone.0034515
pmid:22479638
pmcid:PMC3315547
fatcat:x6lfjh4vxfbqnld73gbycrbfce
Bayesian object matching
2013
Machine Learning
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We learn a Bayesian canonical correlation analysis model that includes a permutation parameter for re-ordering the samples in one of the sets. ...
We provide both variational and sampling-based inference for approximative Bayesian analysis, and demonstrate on three data sets that the resulting methods outperform the earlier solutions. ...
Inference COIN, 251170). ...
doi:10.1007/s10994-013-5357-4
fatcat:j5mby3hmjvgnrbipl364thyjxm
Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks
2009
BMC Bioinformatics
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We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation ...
Conclusion: We concluded that penalized canonical correlation analysis is a powerful tool to identify candidate genes in pathway analysis. ...
To identify a canonical correlation that is large by chance only, we performed a permutation-analysis on the validation sets. ...
doi:10.1186/1471-2105-10-315
pmid:19785734
pmcid:PMC2760886
fatcat:2q6qsl5hxjbydpsa3xfjv5er44
Stimulus-modality independent activation of the brain network for language
[article]
2019
bioRxiv
pre-print
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We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations ...
Acknowledgments
441 We thank Phillip Alday for providing helpful comments. ...
This work was supported by 442 The Netherlands Organisation for Scientific Research (NWO Vidi: 864.14.011, awarded 443 to J.M.S.).
444 ...
doi:10.1101/714998
fatcat:m2fp5dab7bappmat24zprghuuu
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