Research Output per year
Personal profile
Research interests
My research focuses on the development of statistical tools for the analysis of so-called Big Data. These are data that come from multiple sources (for example, questionnaire and genetic data for the same group of persons) and that consist of a huge number of variables (often more than the number of observations, this is high-dimensional). These data elude existing statistical methods. Hence I develop novel methods for exploration and prediction with such data. In 2016 I received a personal grant from the Netherlands Organisation for Scientific Research to stimulate this research (VIDI grant).
Current courses
Click here for my courses.
Teaching
JBM050: Statistical Computing
880260: Computational Statistics
Keywords
- Data Mining
- Statistics
- Methodology And Statistics
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
Data integration
Chemical Compounds
Genes
Chemical Compounds
Unfolding
Mathematics
Data Integration
Mathematics
Singular value decomposition
Chemical Compounds
Gene
Mathematics
Escherichia coli
Chemical Compounds
Functional Genomics
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2005 2018
Bayesian latent class models for the multiple imputation of cross-sectional, multilevel and longitudinal categorical data
Vidotto, D. 2018 s.l.: Proefschriftmaken. 141 p.Research output: Thesis › Doctoral Thesis › Scientific
Open Access
File
Statistical methods
Bayesian multilevel latent class models for the multiple imputation of nested categorical data
Vidotto, D., Vermunt, J. K. & van Deun, K. Oct 2018 In : Journal of Educational and Behavioral Statistics. 43, 5, p. 511-539Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Introducing SNAC: Sparse Network and Component model for integration of multi-source data
Tio, P., Waldorp, L. J. & Van Deun, K. 2018 23 p.Research output: Working paper › Other research output
Obtaining insights from high-dimensional data: Sparse principal covariates regression
Van Deun, K., Crompvoets, E. A. V. & Ceulemans, E. 2018 In : BMC Bioinformatics. 19, 104Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Transcription
High-dimensional Data
Antibodies
Covariates
Genes
RegularizedSCA: Regularized Simultaneous Component Analysis of multiblock data in R
Gu, Z. & Van Deun, K. 29 Oct 2018 (Accepted/In press) In : Behavior Research Methods.Research output: Contribution to journal › Article › Scientific › peer-review