I
Peer reviewed articles | Books | Submitted | Others
or check in Google Scholar. Some preprints can be found on https://arxiv.org/a/nordhausen_k_1.html.
Books:
2. Yi, M. and Nordhausen, K. (editors) (2023): Robust and Multivariate Statistical Methods Festschrift in Honor of David E. Tyler. Springer.
1. Nordhausen, K. and Taskinen, S. (editors) (2015): Modern Nonparametric, Robust and Multivariate Methods. Festschrift in Honour of Hannu Oja, Springer.
Peer reviewed articles
130. Alfons, A., Archimbaud, A., Nordhausen, K. and Ruiz-Gazen, A.: Tandem Clustering with Invariant Coordinate Selection. Accepted for publication in Econometrics and Statistics.
129. Cappello, C., Piccolotto, N., Mühlmann, C., Bögl, M., Filzmoser, P., Miksch, S. and Nordhausen, K.: Visual Interactive Parameter Selection for Temporal Blind Source Separation. Accepted for publication in Journal of Data Science, Statistics, and Visualisation.
128. Archimbaud, A., Boulfani, F., Gendre, X., Nordhausen, K., Ruiz-Gazen, A. and Virta, J.: ICS for Multivariate Functional Anomaly Detection with Applications to Predictive Maintenance and Quality Control. Accepted for publication in Econometrics and Statistics.
127. Dümbgen, L. and Nordhausen, K. (2024): Approximating Symmetrized Estimators of Scatter via Balanced Incomplete U-Statistics. Annals of the Institute of Statistical Mathematics, 76, 185-207.
126. Mühlmann, C., Bachoc, F., Nordhausen, K. and Yi, M. (2024): Test of the Latent Dimension of a Spatial Blind Source Separation Model. Statistica Sinica, 34, 837-865.
125. Sipilä, M., Nordhausen, K. and Taskinen, S. (2024): Nonlinear Blind Source Separation Exploiting Spatial Nonstationarity. Information Sciences, 665, 120365.
124. Artiemjew, P., Cybulski, R., Emamian, M. H., Grzybowski, A,. Jankowski, A., Lanca, C.,
Mehravaran, S., Mlynski, M., Morawski, C., Nordhausen, K., Pärssinen, O. and Ropiak, K. (2024):
Predicting Children’s Myopia Risk: A Monte Carlo Approach to Compare the Performance of
Machine Learning Models. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence, Volume 3, 1092-1099.
123. Piccolotto, N., Bögl, M., Mühlmann, C., Nordhausen, K., Filzmoser, P. , Schmidt, J. and Miksch, S. (2024): Data Type Agnostic Visual Sensitivity Analysis. IEEE Transactions on Visualization and Computer Graphics, 30, 1106-1116.
122. Sipilä, M., Mühlmann, C., Nordhausen, K. and Taskinen, S. (2024): Robust Second-Order Stationary Spatial Blind Source Separation Using Generalized Sign Matrices. Spatial Statistics, 59, 100803.
121. Mühlmann, C., Filzmoser, P. and Nordhausen, K (2024): Spatial Blind Source Separation in the Presence of a Drift. Austrian Journal of Statistics, 53, 48-68.
120. Mühlmann, C., Filzmoser, P. and Nordhausen, K (2024): Local Difference Matrices for Spatial Blind Source Separation. In Bezzeghoud, M., Banerjee, S., Eshagh, M., Benim, A. C., Merkel, B., Kallel, A., Panda, S., Chenchouni, H., Grab, S. and Barbieri, M. (editors), “Selected Studies in Geophysics, Tectonics and Petroleum Geosciences”, 63-65, Springer, Cham.
119. Flumian, L., Matilainen, M., Nordhausen, K. and Taskinen, S. (2024): Stationary Subspace Analysis Based on Second-Order Statistics. Journal of Applied and Computational Mathematics, 436, 115379.
118. Autio, R., Virta, J., Nordhausen, K., Fogelholm, M., Erkkola, M. and Nevalainen, J. (2023): Tensorial Principal Component Analysis in Detecting Purchase Patterns in Loyalty Card Data. Journal of Medical Internet Research, 25, e44599.
117. Kouril, S., de Sousa, J., Facevicova, K., Gardlo, A., Muehlmann, C., Nordhausen, K., Friedecky, D. and Adam, T. (2023): Multivariate Independent Component Analysis Identifies Patients in Newborn Screening Equally to Adjusted Reference Ranges. International Journal of Neonatal Screening, 9, 60.
116. Nordhausen, K. and Ruiz-Gazen, A. (2023): On the Usage of Joint Diagonalization in Multivariate Statistics: Speed Presentation April 2022. Science Talks, 8, 100275.
115. Yi, M. and Nordhausen, K. (2023): Elasso for Estimating the Signal Dimension in ICA. In the proceedings of the 31st European Signal Processing Conference, (EUSIPCO), 2023-2027.
114. Taskinen, S. and Nordhausen, K.: Least Median of Squares (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 728-731, Springer, Cham.
113. Nordhausen, K.: Time Series Analysis in the Geosciences (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 1551-1559, Springer, Cham.
112. Radojicic, U., Nordhausen, K. and Taskinen, S.: Singular Spectrum Analysis (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 1328-1332, Springer, Cham.
111. Radojicic, U. and Nordhausen, K.: Least Absolute Value (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 720-724, Springer, Cham.
110. Nordhausen, K. and Taskinen, S.: Locally Weighted Scatterplot Smoother (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 748-751, Springer, Cham.
109. Taskinen, S. and Nordhausen, K.: Iterative Weighted Least Squares (2023). In Daya Sagar, B. D., Cheng, Q., McKinley, J. and Agterberg, F. (editors), “Encyclopedia of Mathematical Geosciences”, 688-691, Springer, Cham.
108. Mühlmann, C., De Iaco, S. and Nordhausen, K. (2023): Blind Recovery of Sources for Multivariate Space-Time Environmental Data. Stochastic and Environmental Research and Risk Assessment, 37 1593-1613.
107. Taskinen, S., Frahm, G., Nordhausen, K. and Oja, H. (2023). A Review of Tyler’s Shape Matrix and Its Extensions. In: Yi, M. and Nordhausen, K. (editors), “Robust and Multivariate Statistical Methods”, 23-41, Springer, Cham.
106. Fischer, D., Nordhausen, K. and Yi, M. (2023). An Analysis of David E. Tyler’s Publication and Coauthor Network. In: Yi, M. and Nordhausen, K. (editors), “Robust and Multivariate Statistical Methods”, 3-21, Springer, Cham.
105. Archimbaud, A., Drmac, Z., Nordhausen, K., Radojicic, U. and Ruiz-Gazen, A. (2023): Numerical Considerations and a New Implementation for ICS. SIAM Journal on Mathematics of Data Science, 5, 97-121.
104. Nordhausen, K., Taskinen, S. and Virta, J. (2022): Signal Dimension Estimation in BSS Models with Serial Dependence. In the proceedings of the 2nd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 360-366.
103. Piccolotto, N., Bögl, M., Gschwandtner, T., Mühlmann, C., Nordhausen, K., Filzmoser, P. and Miksch, S. (2022): TBSSvis: Visual Analytics for Temporal Blind Source Separation. Visual Informatics, 6, 51-66.
102. Babek, O., Facevicova, K., Zidek, M., Sedlacek, J., Mühlmann, C., Nordhausen, K. and Hron, K. (2022): X-Ray Fluorescence Scanning of Soft and Wet-Sediment Cores for Environmental Risk Assessment; A Robust Blind Source Separation Approach. Journal of Geochemical Exploration, 243, 107106.
101. Hänninen, J., Mäkinen, K., Nordhausen, K., Laaksonlaita, J., Loisa, O. and Virta, J. (2022): The “Seili-index” for the Prediction of Chlorophyll-α Levels in the Archipelago Sea of the Northern Baltic Sea, Southwest Finland. Environmental Modeling & Assessment, 27, 571–584.
100. Piccolotto, N., Bögl, M., Mühlmann, C., Nordhausen, K., Filzmoser, P. and Miksch, S. (2022): Visual Parameter Selection for Spatial Blind Source Separation. Computer Graphics Forum, 41, 157-168.
99. Pan, Y., Matilainen, M., Taskinen, S. and Nordhausen, K. (2022): A Review of Second-Order Blind Identification Methods. WIREs Computational Statistics, 14, e1550.
98. Mühlmann, C., Bachoc, F. and Nordhausen, K. (2022): Blind Source Separation for Non-Stationary Random Fields. Spatial Statistics, 47, 100574.
97. Nordhausen, K., Oja, H. and Tyler, D.E. (2022): Asymptotic and Bootstrap Tests for Subspace Dimension. Journal of Multivariate Analysis, 188, 104830.
96. Nordhausen, K. and Ruiz-Gazen, A. (2022): On the Usage of Joint Diagonalization in Multivariate Statistics. Journal of Multivariate Analysis, 188, 104844.
95. Radojicic, U., Nordhausen, K. and Virta, J. (2021): Large-Sample Properties of Blind Estimation of the Linear Discriminant Using Projection Pursuit. Electronic Journal of Statistics, 15, 6677-6739.
94. Fischer, D., Berro, A.,Nordhausen, K. and Ruiz-Gazen, A. (2021): REPPLab: Detecting Groups and Outliers Using Exploratory Projection Pursuit. Communications in Statistics – Simulation and Computation, 50, 3397-3419.
93. Mühlmann, C., Nordhausen, K. and Yi, M. (2021): On CoKriging, Neural Networks, and Spatial Blind Source Separation for Multivariate Spatial Prediction. IEEE Geoscience and Remote Sensing Letters, 18, 1931-1935.
92. Radojicic, U., Lietzen, N., Nordhausen, K. and Virta, J. (2021): Dimension Estimation in Two-Dimensional PCA. In S. Loncaric, T. Petkovic and D. Petrinovic (editors) “Proceedings of the 12 International Symposium on Image and Signal Processing and Analysis (ISPA 2021)”, 16-22.
91. Nordhausen, K., Fischer, G. and Filzmoser, P. (2021): Blind Source Separation for Compositional Time Series. Mathematical Geosciences, 53, 905-924.
90. Nordhausen, K., Matilainen, M., Miettinen, J., Virta, J. and Taskinen, S. (2021): Dimension Reduction for Time Series in a Blind Source Separation Context Using R. Journal of Statistical Software, 98, 1-30.
89. Mühlmann, C., Facevicova, K., Alzbeta G., Janeckova, H. and Nordhausen, K. (2021): Independent Component Analysis for Compositional Data. In A. Daouia and A. Ruiz-Gazen (editors) “Advances in Contemporary Statistics and Econometrics: Festschrift in Honor of Christine Thomas-Agnan”, 525-545, Springer, Cham.
88. Filzmoser, P. and Nordhausen, K. (2021): Robust Linear Regression for High-dimensional Data: An Overiew. WIREs Computational Statistics, 13, e1524.
87. Virta, J., Lietzen, N., Ilmonen, P. and Nordhausen, K. (2021): Fast Tensorial JADE. Scandinavian Journal of Statistics, 48, 164-187.
86. Virta, J. and Nordhausen, K. (2021): Determining the Signal Dimension in Second Order Source Separation. Statistica Sinica, 31, 135-156.
85. Mühlmann, C., Oja, H. and Nordhausen, K. (2021): Sliced Inverse Regression for Spatial Data. In E. Bura and B. Li (editors) “Festschrift in Honor of R. Dennis Cook: Fifty Years of Contribution to Statistical Science”, 87-107, Springer, Cham.
84. Fischer, D., Nordhausen, K. and Oja, H. (2020): On Linear Dimension Reduction Based on Diagonalization of Scatter Matrices for Bioinformatics Downstream Analyses. Heliyon, 6, e05732.
83. Bachoc, F., Genton, M.G., Nordhausen, K., Ruiz-Gazen, A. and Virta, J. (2020): Spatial Blind Source Separation. Biometrika, 107, 627-646.
82. Radojicic, U. and Nordhausen, K. (2020): Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace. In Maciak, M., Pestas, M. and Schindler, M. (editors) “Analytical Methods in Statistics. AMISTAT 2019”, 101-123, Springer, Cham.
81. Radojicic, U., Nordhausen, K., and Oja, H. (2020): Notion of Information and Independent Component Analysis. Applications of Mathematics, 65, 311-330.
80. Taurio, J., Järvinen, J., Hautaniemi, E.J., Eräranta, A., Viitala, J., Nordhausen, K., Kaukinen, K., Mustonen, J. and Pörsti, I. (2020): Team-based “Get-a-Grip” Lifestyle Management Programme in the Treatment of Obesity. Preventive Medicine Reports, 19, 101119.
79. Lietzen, N., Virta, J., Nordhausen, K. and Ilmonen, P. (2020): Minimum Distance Index for BSS, Generalization, Interpretation and Asymptotics. Austrian Journal of Statistics, 49, 57-68.
78. Fischer, D., Mosler, K., Möttönen, J., Nordhausen, K., Pokotylo, O. and Vogel, D. (2020): Computing the Oja Median in R: The Package OjaNP. Journal of Statistical Software, 92, 1-36.
77. Miettinen, M., Matilainen, M., Nordhausen, K. and Taskinen, S. (2020): Extracting Conditionally Heteroskedastic Components Using Independent Component Analysis. Journal of Time Series Analysis, 41, 293-311.
76. Virta, J., Li, B., Nordhausen, K. and Oja, H. (2020): Independent Component Analysis for Multivariate Functional Data. Journal of Multivariate Analysis, 176, 104568.
75. Frahm, G., Nordhausen, K. and Oja, H. (2020): M-Estimation of Location and Scatter with Incomplete and Dependent Data. Journal of Multivariate Analysis, 176, 104569.
74. Lietzen, N., Virta, J., Nordhausen, K. and Ilmonen, P. (2019): Minimum Distance Index for Non-Square Complex Valued Mixing Matrices. In Filzmoser, P. and Kharin, Y. (editors) “Proceedings of the 12th International Conference on Computer Data Analysis and Modeling”, 79-86, Minsk Publishing Center BSU, Minsk.
73. Virta, J. and Nordhausen, K. (2019): Estimating the Number of Signals Using Principal Component Analysis. Stat, 8, e231.
72. Matilainen, M., Croux, C., Nordhausen, K. and Oja, H. (2019): Sliced Average Variance Estimation for Multivariate Time Series. Statistics: A Journal of Theoretical and Applied Statistics, 53, 630-655.
71. Nordhausen, K. and Virta, J. (2019): An Overview of Properties and Extensions of FOBI. Knowledge-Based Systems, 173, 113-116.
70. Miettinen, J., Nordhausen, K. and Taskinen, S. (2018): fICA: FastICA Algorithms and Their Improved Variants. The R Journal, 10, 148-158.
69. Virta, J., Li, B., Nordhausen, K. and Oja, H. (2018): JADE for Tensor-Valued Observations. Journal of Computational and Graphical Statistics, 27, 628-637.
68. Nordhausen, K. and Virta, J. (2018): Ladle Estimator for Time Series Signal Dimension. Proceedings of the IEEE Statistical Signal Processing Workshop (SSP), 428-432.
67. Archimbaud, A., Nordhausen, K. and Ruiz-Gazen, A. (2018): Unsupervized Outlier Detection with ICSOutlier. The R Journal, 10, 234-250.
66. Archimbaud, A., Nordhausen, K. and Ruiz-Gazen, A. (2018): ICS for Multivariate Outlier Detection with Application to Quality Control. Computational Statistics and Data Analysis, 128, 184-199.
65. Nordhausen, K. and Oja, H. (2018): Independent Component Analysis: A Statistical Perspective. WIREs Computational Statistics, 10, e1440.
64. Matilainen, M., Nordhausen, K. and Virta, J. (2018): On the Number of Signals in Multivariate Time Series. In Deville, Y., Gannot, S., Mason, R., Plumbley, M.D. and Ward, D. (editors) “International Conference on Latent Variable Analysis and Signal Separation”, LNCS 10891, 248-258. Springer, Cham.
63. Teschendorff, A.E., Han, J., Paul, D., Virta, J. and Nordhausen, K. (2018): Tensorial Blind Source Separation for Improved Analysis of Multi-Omic Data. Genome Biology, 19, 76.
62. Nordhausen, K. and Oja, H. (2018): Robust Nonparametric Inference. Annual Review of Statistics and Its Application, 5, 473-500.
61. Virta, J. and Nordhausen, K. (2017): Blind Source Separation For Nonstationary Tensor-Valued Time Series. Proceedings of the 27th International IEEE Workshop on Machine Learning for Signal Processing (MLSP), 1-6.
60. Virta, J., Li, B., Nordhausen, K. and Oja, H. (2017): Independent Component Analysis for Tensor-Valued Data. Journal of Multivariate Analysis, 162, 172-192.
59. Matilainen, M., Croux, C., Nordhausen, K. and Oja, H. (2017): Supervised Dimension Reduction for Multivariate Time Series. Econometrics and Statistics, 4, 57-69.
58. Virta, J. and Nordhausen, K. (2017): Blind Source Separation of Tensor-Valued Time Series. Signal Processing, 141, 204-216.
57. Nordhausen, K., Oja, H., Tyler, D.E. and Virta, J. (2017): Asymptotic and Bootstrap Tests for the Dimension of the Non-Gaussian Subspace. Signal Processing Letters, 24, 887-891.
56. Matilainen, M., Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2017): On Independent Component Analysis and Stochastic Volatility Models. Austrian Journal of Statistics, 46, 57-66.
55. Fischer, D., Honkatukia, M., Tuiskula-Haavisto, M., Nordhausen, K., Cavero, D., Preisinger, R. and Vilkki, J. (2017): Subgroup Detection in Genotype Data Using Invariant Coordinate Selection. BMC Bioinformatics, 18, 173.
54. Virta, J. and Nordhausen, K. (2017): On the Optimal Nonlinearities for Gaussian Mixtures in FastICA. In Tichavsky P., Babaie-Zadeh M., Michel O. and Thirion-Moreau N. (editors) “Latent Variable Analysis and Signal Separation”, LNCS 10169, 427-437, Springer, Cham.
53. Lietzen, N., Nordhausen, K. and Ilmonen, P. (2017): Complex Valued Robust Multidimensional SOBI. In Tichavsky P., Babaie-Zadeh M., Michel O. and Thirion-Moreau N. (editors) “Latent Variable Analysis and Signal Separation”, LNCS 10169, 131-140, Springer, Cham.
52. Miettinen, J., Nordhausen, K. and Taskinen, S. (2017): Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp. Journal of Statistical Software, 76, 1-31.
51. Miettinen, J., Nordhausen, K., Oja, H., Taskinen, S. and Virta, J. (2017): The Squared Symmetric FastICA Estimator. Signal Processing, 131, 402-411.
50. Virta, J., Taskinen, S. and Nordhausen, K. (2016): Applying Fully Tensorial ICA to fMRI Data. In the Proceedings of the IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1-6.
49. Miettinen, J., Nordhausen, K., Taskinen, S. and Tyler, D.E. (2016): On the Computation of Symmetrized M-Estimators of Scatter. In Agostinelli, C., Basu, A., Filzmoser, P. and Mukherje, D. (editors) “Recent Advances in Robust Statistics: Theory and Applications”, 131-149, Springer India, New Delhi.
48. Liski, E., Nordhausen, K., Oja, H. and Ruiz-Gazen, A. (2016): Combining Linear Dimension Reduction Subspaces. In Agostinelli, C., Basu, A., Filzmoser, P. and Mukherje, D. (editors) “Recent Advances in Robust Statistics: Theory and Applications”, 151-167, Springer India, New Delhi.
47. Matilainen, M., Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2016): ICA and Stochastic Volatility Models. In Aivazian, S., Filzmoser, P. and Kharin, Y.: “Proceedings of the XI International Conference on Computer Data Analysis and Modeling”, 30-37, Publishing Center of BSU, Minsk.
46. Lietzen, N., Nordhausen, K. and Ilmonen, P. (2016): Minimum Distance Index for Complex Valued ICA. Statistics and Probability Letters, 118, 100-106.
45. Tahvanainen, A., Tikkakoski, A., Koskela, J., Nordhausen, K., Viitala, J., Leskinen, M., Kähönen, M., Kööbi, T., Uito, M., Viik, J., Mustonen, J. and Pörsti, I. (2016) : The Type of the Functional Cardiovascular Response to Upright Posture is Associated With Arterial Stiffness: A Cross-Sectional Study in 470 Volunteers. BMC Cardiovascular Disorders, 16, 1-12.
44. Taskinen, S., Miettinen, J. and Nordhausen, K. (2016): A More Effcient Second Order Blind Identification Method for Separation of Uncorrelated Stationary Time Series. Statistics and Probability Letters, 116, 121-126.
43. Miettinen, J., Illner, K., Nordhausen, K., Oja, H., Taskinen, S. and Theis, F.J. (2016): Separation of Uncorrelated Stationary Time Series Using Autocovariance Matrices. Journal of Time Series Analysis, 37, 337-354.
42. Dümbgen, L., Nordhausen, K. and Schuhmacher, H. (2016): New Algorithms for M-estimation of Multivariate Location and Scatter. Journal of Multivariate Analysis, 144, 200-217.
41. Fischer, D., Nordhausen, K. and Taskinen, S. (2015): Publication and Coauthorship Networks of Hannu Oja. In Nordhausen, K. and Taskinen, S. (editors) “Modern Nonparametric, Robust and Multivariate Methods. Festschrift in Honour of Hannu Oja”, 7-27, Springer.
40. Ilmonen, P., Nordhausen, K., Oja, H. and Theis, F.J. (2015): An Affine Equivariant Robust Second Order Blind Source Separation Method. In Vincent, E., Yeredor, A., Koldovsky, Z. and Tichavsky, P. (editors) “Latent Variable Analysis and Signal Separation”, LNCS 9237, 328-335, Springer.
39. Nordhausen, K., Oja, H. and Pärssinen, O. (2015): Mixed Effects Regression Splines to Model Myopia Data. Journal of Biometrics and Biostatistics, 6, 239.
38. Nordhausen, K. and Tyler, D.E. (2015): A Cautionary Note on Robust Covariance Plug-in Methods. Biometrika, 102, 573-588.
37. Nordhausen, K., Oja, H., Filzmoser, P. and Reimann, C. (2015): Blind Source Separation for Spatially Correlated Compositional Data. Mathematical Geosciences, 47, 753-770.
36. Miettinen, J., Taskinen, S., Nordhausen, K. and Oja, H. (2015): Fourth Moments and Independent Component Analysis. Statistical Science, 30, 372-390.
35. Hautaniemi, E., Tikkakoski, A., Tahvanainen A., Nordhausen, K., Kähönen, M., Mattsson, T., Luhtala, S., Turpeinen, A., Vapaatalo, H., Korpela, R. and Pörsti, I. (2015): Effect of Fermented Milk Product Containing Lactotripeptides and Plant Sterol Esters on Haemodynamics in Subjects with Metabolic Syndrome – a Randomized, Double-blinded, Placebo-controlled Study. British Journal of Nutrition, 114, 376-386.
34. Haltia, O., Törmänen, S., Eräranta, A., Jokihaara, J., Nordhausen, K., Rysä, J., Ruskoaho, H., Tikkanen, I., Mustonen, J. and Pörsti, I. (2015): Vasopeptidase Inhibition Corrects Structure and Function of Small Arteries in Experimental Renal Insufficiency. Journal of Vascular Research, 52, 94-102.
33. Matilainen, M., Nordhausen, K. and Oja, H. (2015): New Independent Component Analysis Tools for Time Series. Statistics and Probability Letters, 105, 80-87.
32. Illner, K., Miettinen, J., Fuchs, C., Taskinen, S., Nordhausen, K., Oja, H. and Theis, F.J. (2015): Model Selection Using Limiting Distributions of Second-order Source Separation Algorithms. Signal Processing, 113, 95-103.
31. Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2014): Deflation-based FastICA with Adaptive Choices of Nonlinearities. IEEE Transaction on Signal Processing, 62, 5716-5724.
30. Liski, E., Nordhausen, K. and Oja, H. (2014): Supervised Invariant Coordinate Selection. Statistics: A Journal of Theoretical and Applied Statistics, 48, 711-731.
29. Nordhausen, K. (2014): On Robustifying Some Second Order Blind Source Separation Methods for Nonstationary Time Series. Statistical Papers, 55, 141-156.
28. Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2014): Deflation-based Separation of Uncorrelated Stationary Time Series. Journal of Multivariate Analysis, 123, 214-227.
27. Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2013): Fast Equivariant JADE. In the Proceedings of 38th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 6153-6157.
26. Oja, H. and Nordhausen, K. (2012): Independent Component Analysis. In El-Shaarawi, A.-H. and Piegorsch, W. (editors) “Encyclopedia of Environmetrics”, 2nd Edition, 1352-1360, Chichester, UK.
25. Miettinen, J., Nordhausen, K., Oja, H. and Taskinen, S. (2012): Statistical Properties of a Blind Source Separation Estimator for Stationary Time Series. Statistics & Probability Letters, 82, 1865-1873.
24. Nordhausen, K., Gutch, H. W., Oja, H. and Theis, F.J. (2012): Joint Diagonalization of Several Scatter Matrices for ICA. In Theis, F., Cichocki, A., Yeredor, A. and Zibulevsky, M. (editors) “Latent Variable Analysis and Signal Separation”, LNCS 7191, 172-179, Springer, Berlin Heidelberg.
23. Tahvanainen, A., Tikkakoski, A., Leskinen, M., Nordhausen, K., Kähönen, M., Kööbi, T., Mustonen, J. and Pörsti, I. (2012): Supine and Upright Haemodynamic Effects of Sublingual Nitroglycerin and Inhaled Salbutamol – a Double-blind, Placebo-controlled, Randomized Study. Journal of Hypertension, 30(2), 297-306.
22. Nordhausen, K. and Oja, H. (2011): Discussion on the paper “The Asymptotic Efficiency of the Spatial Median for Elliptically Symmetric Distributions” by Andrew Magyar and David E. Tyler. Sankhya, Series B, 73, 188-191.
21. Nordhausen, K., Ilmonen, P., Mandal, A., Oja, H. and Ollila, E. (2011): Deflation-based FastICA Reloaded. In the Proceedings of “19th European Signal Processing Conference 2011 (EUSIPCO 2011)”, 1854-1858.
20. Nordhausen, K. and Oja, H. (2011): Scatter Matrices with Independent Block Property and ISA. In the Proceedings of “19th European Signal Processing Conference 2011 (EUSIPCO 2011)”, 1738-1742.
19. Nordhausen, K. and Oja, H. (2011): Multivariate L1 Methods: The Package MNM. Journal of Statistical Software, 43(5), 1-28.
18. Nordhausen, K., Ollila, E. and Oja, H. (2011): On the Performance Indices of ICA and Blind Source Separation. In the Proceedings of “2011 IEEE 12th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2011)”, 486-490.
17. Nordhausen, K. and Oja, H. (2011): Independent Subspace Analysis using Three Scatter Matrices. Austrian Journal of Statistics, 40 (1&2), 93-101.
16. Tahvanainen, A., Koskela, J., Leskinen, M., Ilveskoski, E., Nordhausen, K., Kähönen, M., Kööbi, T., Mustonen, J. and Pörsti, I. (2011): Reduced Systemic Vascular Resistance in Healthy Volunteers with Presyncopal Symptoms During Nitrate-Stimulated Tilt-Table Test. British Journal of Clinical Pharmacology, 71, 41-51.
15. Nordhausen, K., Oja, H. and Ollila, E. (2011): Multivariate Models and the First Four Moments. In Hunter, D.R., Richards, D.S.R. and Rosenberger, J.L. (editors) “Nonparametric Statistics and Mixture Models: A Festschrift in Honor of Thomas P. Hettmansperger”, 267-287, World Scientific, Singapore.
14. Möttönen, J., Nordhausen, K. and Oja, H. (2010): Asymptotic Theory of the Spatial Median. In Antoch, J., Huskova, M. and Sen, P.K. (editors) “Nonparametrics and Robustness in Modern Statistical Inference and Time Series Analysis: A Festschrift in Honor of Professor Jana Jureckova”, 182–193, IMS Collections, Vol. 7.
13. Ilmonen, P., Nordhausen, K., Oja, H. and Ollila, E. (2010): A New Performance Index for ICA: Properties, Computation and Asymptotic Analysis. In Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R. and Vincent, E. (editors) “Latent Variable Analysis and Signal Separation”, LNCS 6365, 229-236, Springer, Heidelberg.
12. Nordhausen, K. and Oja, H. (2010): Three Scatter Matrices and Independent Subspace Analysis. In Aivazian, S. , Filzmoser, P. and Kharin, Y. (editors) “Proceedings of the 9th International Conference on Computer Data Analysis and Modeling”, 93-100, Minsk Publishing Center BSU, Minsk.
11. Puolakka, P.A.E., Rorarius, M.G.F., Roviola, M., Puolakka, T.J.S., Nordhausen, K. and Lindgren, L. (2010): Persistent Pain Following Knee Arthroplasty. European Journal of Anaesthesiology, 27, 455-460.
10. Tahvanainen, A., Leskinen, M., Koskela, J., Ilveskoski, E., Nordhausen, K., Oja, H., Kähönen, M., Kööbi, T., Mustonen, J. and Pörsti, I. (2009): Ageing and Cardiovascular Responses to Head-Up Tilt in Healthy Subjects. Atherosclerosis, 207, 445-451.
9. Nordhausen, K., Oja, H. and Paindaveine, D. (2009): Signed-Rank Tests for Location in the Symmetric Independent Component Model. Journal of Multivariate Analysis, 100(5), 821-834.
8. Nordhausen, K., Oja, H. and Tyler, D.E. (2008): Tools for Exploring Multivariate Data: The Package ICS. Journal of Statistical Software, 28(6), 1-31.
7. Nordhausen, K., Oja, H. and Ollila, E. (2008): Robust Independent Component Analysis Based on Two Scatter Matrices. Austrian Journal of Statistics, 37(1), 91-100.
6. Nordhausen, K., Oja, H. and Ollila, E. (2007): Robust ICA Based on Two Scatter Matrices. In Aivazian, S. , Filzmoser, P. and Kharin, Y. (editors) “Proceedings of the 8th International Conference on Computer Data Analysis and Modeling”, 84-91, Minsk Publishing Center BSU, Minsk.
5. Nordhausen, K. and Nummi, T. (2007): Estimation of the Diameter Distribution of a Stand Marked for Cutting Using Finite Mixtures. Canadian Journal of Forest Research, 37(4), 817-824.
4. Nordhausen, K. and Sinha, B.K. (2006): ML Estimation for a Pareto Distribution of the Second Kind in a Sequential Design. Journal of the Indian Statistical Association, 44(1), 61-72.
3. Kukkasjärvi, P., Nordhausen, K. and Malmivaara, A. (2006): Reanalysis of Systematic Reviews: The Case of Invasive Strategies for Acute Coronary Syndromes, International Journal of Technology Assessment in Health Care, 22(4), 484-496.
2. Aula, A. and Nordhausen, K. (2006): Modeling Successful Performance in Web Searching, Journal of the American Society for Information Science and Technology, 57(12), 1678-1693.
1. Nordhausen, K., Oja, H. and Tyler, D.E. (2006): On the Efficiency of Invariant Multivariate Sign and Rank Tests. In Liski, E.P., Isotalo, J., Niemelä, J., Puntanen, S., and Styan, G.P.H. (editors) “Festschrift for Tarmo Pukkila on his 60th birthday”, 217-231, University of Tampere, Tampere.
Unpublished preprints:
2. Virta, J., Nordhausen, K. and Oja, H.: Joint Use of Third and Fourth Cumulants in Independent Component Analysis. arXiv
1. Ilmonen, P., Nordhausen, K., Oja, H. and Ollila, E.: On Asymptotics of ICA Estimators and Their Performance Indices. arXiv
Submitted manuscripts:
10. Virta, J., Nagy, S. and Nordhausen, K.: Projection-Based Estimators for Tensor Data.
9. De Iaco, S., Cappello, S., Congedi, A., Palma, M. and Nordhausen, K.: A Multivariate Approach for Modeling Spatio-Temporal Agrometeorological Variables.
8. Möttönen, J., Nordhausen, K., Oja, H. and Radojicic, U.: The Asymptotic Properties of the One-Sample Spatial Rank Methods.
7. Bachoc, F., Mühlmann, C., Nordhausen, K., and Virta, J.: Large-Sample Properties of Non-Stationary Source Separation for Gaussian Signals.
6. Radojicic, U., Lietzen, N., Nordhausen, K. and Virta, J.: Order Determination for Tensor-valued Observations Using Data Augmentation.
5. Radojicic, U., Nordhausen, K. and Virta, J.: Kurtosis-Based Projection Pursuit for Matrix-Valued Data.
4. Mühlmann, C., Cappello, C., De Iaco, S. and Nordhausen, K.: Anisotropic Local Covariance Matrices for Spatial Blind Source Separation.
3. Nordhausen, K. and Taskinen, S.: Independent Component Analysis.
2. Nordhausen: Invariant Coordinate Selection.
1. Virta, J., Nordhausen, K. and Oja, H.: Projection Pursuit for Non-Gaussian Independent Components. arXiv
12. Lanca, C., Pärssinen, O., Mehravaran, S., Nordhausen, K., Emamian, M. H. and Grzybowski, A. (2023): Comment on: Development and Validation of a Novel Nomogram for Predicting the Occurrence of Myopia in Schoolchildren: A Prospective Cohort Study. American Journal of Ophthalmology, 246, 273-274.
11. Nordhausen, K., Ollila, E. and Taskinen, S. (2017): To Make, Or Not to Make Any Moment Assumptions? In The Yearbook of the Finnish Statistical Society 2015-2016.
10. Nordhausen, K. (2015): Book review of “Statistical Analysis of Network Data with R” by E.D. Kolaczyk and G. Csardi. International Statistical Reviews, Short Book Reviews, 83(1), 171-172.
9. Nordhausen, K. (2014): Book review of “An Introduction to Statistical Learning – with Applications in R” by G. James, D. Witten, T. Hastie and R. Tibshirani. International Statistical Reviews, Short Book Reviews, 82(1), 156-157.
8. Nordhausen, K. (2014): Book review of “Multiple Imputation and its Application” by J. R. Carpenter and M. G. Kenward. International Statistical Reviews, Short Book Reviews, 82(1), 151-152.
7. Nordhausen, K. (2013): Book review of “Ensemble Methods: Foundations and Algorithms” by Z.-H. Zho. International Statistical Reviews, Short Book Reviews, 81(3), 470.
6. Nordhausen, K. (2013): Book review of “Stationary Stochastic Processes” by G. Lindgren. International Statistical Reviews, Short Book Reviews, 81(3), 469-470.
5. Nordhausen, K. (2009): Book review of “The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition” by T. Hastie, R. Tibshirani and J. Friedman. International Statistical Reviews, Short Book Reviews, 77(3), 482.
4. Nordhausen, K. (2008): On Invariant Coordinate Selection and Nonparametric Analysis of Multivatiate Data, Dissertation, Tampere University Press, Tampere. link
3. Nordhausen, K. (2008): Two Scatter Matrices for Multivariate Analysis. In Koivisto, P. (editor) “Digest of TISE Seminar 2008”, 34-39, Tampere.
2. Fischer, M., Moriarty J., Nordhausen, K., Panov, I. and Vecil, F. (2006): Dynamic Traffic Control. In Heiliö, M. and Kauranne, T. (editors) “Proceedings of the 18th ECMI Modelling Week 13.-21. August 2004”, 39-47, Research Report 101, Lappeenranta University of Technology, Lappeenranta.
1. Nordhausen, K. (2003): Comparison Between Empirical Bayes and Fully Bayes approaches for Conditionally Exponential Distributed Data, Diploma Thesis, Department of Statistics, University of Dortmund.