Sara Taskinen

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ORCID link: http://orcid.org/0000-0001-9470-7258

Active JYU affiliations

Department of Mathematics and Statistics, Senior Lecturer

Previous or other affiliations

Sara Ahola, Department of Mathematics and Statistics (University of Jyväskylä), Senior Lecturer

Research interests

We develop new, efficient statistical methods which can be used when analysing very high-dimensional and complex multivariate data. The methods will be mainly applied to ecological and brain-imaging data.

Fields of science

112 Statistics and probability (Natural sciences)

Publications

A review of second‐order blind identification methods (2021) Pan, Yan; et al.; A2; OA
Extracting conditionally heteroskedastic components using independent component analysis (2020) Miettinen, Jari; et al.; A1; OA
Efficient estimation of generalized linear latent variable models (2019) Niku, Jenni; et al.; A1; OA
gllvm : Fast analysis of multivariate abundance data with generalized linear latent variable models in R (2019) Niku, Jenni; et al.; A1; OA
What information should I look for again? : Attentional difficulties distracts reading of task assignments (2019) Hautala, Jarkko; et al.; A1; OA
fICA : FastICA Algorithms and Their Improved Variants (2018) Miettinen, Jari; et al.; A1; OA
Testate amoebae community analysis as a tool to assess biological impacts of peatland use (2018) Daza Secco, Emmanuella; et al.; A1; OA
Blind Source Separation Based on Joint Diagonalization in R : The Packages JADE and BSSasymp (2017) Miettinen, Jari; et al.; A1; OA
Generalized linear latent variable models for multivariate count and biomass data in ecology (2017) Niku, Jenni; et al.; A1
On Independent Component Analysis with Stochastic Volatility Models (2017) Matilainen, Markus; et al.; A1; OA
The squared symmetric FastICA estimator (2017) Miettinen, Jari; et al.; A1; OA
Variational Approximations for Generalized Linear Latent Variable Models (2017) Hui, Francis K. C.; et al.; A1; OA
Affine-invariant rank tests for multivariate independence in independent component models (2016) Oja, Hannu; et al.; A1; OA
A more efficient second order blind identification method for separation of uncorrelated stationary time series (2016) Taskinen, Sara; et al.; A1; OA
Applying fully tensorial ICA to fMRI data (2016) Virta, Joni; et al.; A4; OA
Extending Joint Models in Community Ecology : A Response to Beissinger et al. (2016) Warton, David I.; et al.; B1
ICA and stochastic volatility models (2016) Matilainen, M.; et al.; A4; OA
Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression (2016) Taskinen, Sara; et al.; A3
On the Computation of Symmetrized M-Estimators of Scatter (2016) Miettinen, Jari; et al.; A3; OA
Separation of Uncorrelated Stationary time series using Autocovariance Matrices (2016) Miettinen, Jari; et al.; A1; OA