1 |
Hubert M, Rousseeuw PJ, and Vanden Branden K (2005). ROBPCA:A new approach to robust principal component analysis, American Statistical Association and the American Society for Quality, 47.
|
2 |
Hyvarinen A (1999). Fast and robust fixed-point algorithms for independent component analysis, IEEE Transactions on Neural Networks, 10, 626-634.
DOI
|
3 |
Hyvarinen A (2013). Independent component analysis: recent advances, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371, 20110534.
DOI
|
4 |
Langlois D, Chartier S, and Gosselin D (2010). An introduction to independent component analysis: infoMax and fastICA algorithms, Tutorials in Quantitative Methods for Psychology, 6, 31-38.
DOI
|
5 |
McKeown MJ, Jung TP, Makeig S, Brown G, Kindermann SS, Lee TW, and Sejnowski TJ (1998). Spatially independent activity patterns in functional MRI data during the stroop color-naming task. In Proceedings of the National Academy of Sciences, 95, 803-810.
DOI
|
6 |
Rousseeuw PJ (1984). Least median of squares regression, Journal of the American Statistical Association, 89, 871-880.
DOI
|
7 |
Rousseeuw PJ and Driessen KV (1999). A fast algorithm for the minimum covariance determinant estimator, Technometrics, 41, 212-223.
DOI
|
8 |
Todorov V (2009). Rrcov: scalable robust estimators with high breakdown point, r package version 0.5-03. Available from: http://CRAN.R-project.org/package=rrcov.
|
9 |
Calhoun VD, Adali T, Pearlson GD, and Pekar JJ (2001). A method for making group inferences from functional MRI data using independent component analysis, Human Brain Mapping, 14, 140-151.
DOI
|
10 |
Hyvarinen A and Oja E (2000). Independent component analysis: algorithms and applications, Journal of Neural Networks, 13, 411-430.
DOI
|
11 |
De Klerk J (2015). Time series outlier detection using the trajectory matrix in singular spectrum analysis with outlier maps and ROBPCA, South African Statistical Journal, 49, 61-76.
|
12 |
Bai P, Shen H, Huang X, and Truong Y (2008). A supervised singular value decomposition for independent component analysis for fMRI, Statistica Sinica, 18, 1233-1252.
|
13 |
McKeown MJ and Sejnowski TJ (1998). Independent component analysis of FMRI data: examining the assumptions, Human Brain Mapping 6, 368-372.
DOI
|
14 |
Meinecke FC, Harmeling S, and Muller KR (2004). Robust ICA for super-Gaussian sources, In International Conference on Independent Component Analysis and Signal Separation, 17-224, Springer, Berlin, Heidelberg.
|
15 |
Pruim RH, Mennes M, van Rooij D, Llera A, Buitelaar JK, and Beckmann CF (2015). ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data, Neuroimage, 112, 267-277.
DOI
|
16 |
Rachakonda S, Egolf E, Correa N, and Calhoun V (2007). Group ICA of fMRI toolbox (GIFT) manual. Available from: http://www.nitrc.org/docman/view.php/55/295.
|
17 |
Biswal BB and Ulmer JL (1999). Blind source separation of multiple signal sources of fMRI data sets using independent component analysis, Journal of Computer Assisted Tomography, 23, 265-271.
DOI
|
18 |
Bordier C, Dojat M, and de Micheaux PL (2011). Temporal and spatial independent component analysis for fMRI data sets embedded in the AnalyzeFMRI r package, Journal of Statistical Software, 44, 1-24.
|
19 |
Bulut H and Oner Y (2017). The evaluation of socio-economic development of development agency regions in Turkey using classical and robust principal component analyses, Journal of Applied Statistics, 44, 2936- 2948.
DOI
|
20 |
Comon P (1994). Independent component analysis, a new concept?, Signal Processing, 36, 287-314.
DOI
|