Cover Image

Cellwise robust and sparse principal component analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pfeiffer, Pia, Vana-Gür, Laura, Filzmoser, Peter
Format:	Preprint
Published:	2024
Subjects:	Computation Applications Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

spar: Sparse Projected Averaged Regression in R
by: Parzer, Roman, et al.
Published: (2024)

Data-Driven Random Projection and Screening for High-Dimensional Generalized Linear Models
by: Parzer, Roman, et al.
Published: (2024)

Sparse Data-Driven Random Projection in Regression for High-Dimensional Data
by: Parzer, Roman, et al.
Published: (2023)

Sparse group principal component analysis via double thresholding with application to multi-cellular programs
by: Xu, Qi, et al.
Published: (2026)

Efficient Bayesian functional principal component analysis of irregularly-observed multivariate curves
by: Nolan, Tui, et al.
Published: (2023)

Multivariate ordinal regression for multiple repeated measurements
by: Vana-Gür, Laura
Published: (2024)

Fast and robust invariant generalized linear models
by: Knight, Parker, et al.
Published: (2025)

FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis
by: Ma, Ziling, et al.
Published: (2025)

Another look at forecast trimming for combinations: robustness, accuracy and diversity
by: Wang, Xiaoqian, et al.
Published: (2022)

Differential item functioning via robust scaling
by: Halpin, Peter F.
Published: (2022)

Two-phase validation sampling via principal components to improve efficiency in multi-model estimation from error-prone biomedical databases
by: Lotspeich, Sarah C., et al.
Published: (2025)

The permuted score test for robust differential expression analysis
by: Barry, Timothy, et al.
Published: (2025)

Regularizing threshold priors with sparse response patterns in Bayesian factor analysis with categorical indicators
by: Padgett, R. Noah, et al.
Published: (2023)

Multiply robust estimation for causal survival analysis with treatment noncompliance
by: Cheng, Chao, et al.
Published: (2023)

Multipopulation mortality modelling and forecasting: The multivariate functional principal component with time weightings approaches
by: Lam, Ka Kin, et al.
Published: (2021)

Doubly robust omnibus sensitivity analysis of externally controlled trials with intercurrent events
by: Gao, Chenyin, et al.
Published: (2025)

A joint model of correlated ordinal and continuous variables
by: Vana-Gür, Laura, et al.
Published: (2024)

Boosting with copula-based components
by: Brant, Simon Boge, et al.
Published: (2022)

Bayesian network-guided sparse regression with flexible varying effects
by: Ren, Yangfan, et al.
Published: (2024)

Bayesian principal stratification with longitudinal data and truncation by death
by: Grossi, Giulio, et al.
Published: (2023)

Reliability analysis of arbitrary systems based on active learning and global sensitivity analysis
by: Moustapha, Maliki, et al.
Published: (2023)

Gender disparities in rehospitalisations after coronary artery bypass grafting: evidence from a sparse functional causal mediation analysis of the MIMIC-IV data
by: Xu, Henan, et al.
Published: (2024)

Projection-based two-sample inference for sparsely observed multivariate functional data
by: Koner, Salil, et al.
Published: (2023)

Locally sparse varying coefficient mixed model with application to longitudinal microbiome differential abundance
by: Fontaine, Simon, et al.
Published: (2026)

Strategic analysis of hydrogen market dynamics across collaboration models
by: Asghari, Mohammad, et al.
Published: (2025)

A novel smoothing-based goodness-of-fit test of covariance for multivariate sparse functional data
by: Ghosh, Dhrubajyoti, et al.
Published: (2025)

Cellwise Robust Discriminant Analysis
by: Centofanti, Fabio, et al.
Published: (2026)

Reliability analysis for data-driven noisy models using active learning
by: Pires, Anderson V., et al.
Published: (2024)

On regional treatment effect assessment using robust MAP priors
by: Zhang, Xin, et al.
Published: (2026)

Cheap Subsampling bootstrap confidence intervals for fast and robust inference
by: Ohlendorff, Johan Sebastian, et al.
Published: (2025)

Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies
by: Sidrow, Evan, et al.
Published: (2024)

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data
by: Miah, Kaya, et al.
Published: (2024)

Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science
by: Janssen, Joseph, et al.
Published: (2023)

Efficient scenario analysis in real-time Bayesian election forecasting via sequential meta-posterior sampling
by: Han, Geonhee, et al.
Published: (2025)

Increasing power and robustness in screening trials by testing stored specimens in the control arm
by: Katki, Hormuzd A., et al.
Published: (2024)

Bayesian sample size determination using robust commensurate priors with interpretable discrepancy weights
by: Whitehead, Lou E., et al.
Published: (2024)

Confounder-robust causal discovery and inference in Perturb-seq using proxy and instrumental variables
by: Park, Kwangmoon, et al.
Published: (2026)

Multiple Imputation Method for High-Dimensional Neuroimaging Data
by: Lu, Tong, et al.
Published: (2023)

Everything all at once: On choosing an estimand for multi-component environmental exposures
by: Rudolph, Kara E., et al.
Published: (2025)

Spatiotemporal clustering of GHGs emissions in Europe: exploring the role of spatial component
by: Morelli, Caterina, et al.
Published: (2025)