Estimate Dynamic Factor Models with Sparse Loadings

Sparse and Regularized Discriminant Analysis

Computation of Sparse Eigenvectors of a Matrix

Functional Linear Mixed Models for Irregularly or Sparsely
Sampled Data

Sparse Generalized Factor Models with Multiple Penalty Functions

R package sparseHessianFD version 0.3.3.7

Design of Portfolio of Stocks to Track an Index
R package sparseIndexTracking version 0.1.1

Computation of the Sparse Inverse Subset

The Sparse Latent Position Model for Nonnegative Interaction
Data

Represent and Use Sparse + Low Rank Matrices

RcppEigen back end for sparse least trimmed squares regression
R package sparseLTSEigen version 0.2.0.1

SPAtial Resolution-SEnsitive Models of Outbreak Dynamics

'Multiple Systems Estimation for Sparse Capture Data'

Multivariate Normal Functions for Sparse Covariance and
Precision Matrices

Fit Sparse Linear Regression Models via Nonconvex Optimization

Sparse Principal Component Analysis (SPCA)

Variable Selection under Ranked Sparsity Principles for
Interactions and Polynomials
R package sparseR version 0.3.2

Sparse Bayesian Models for Regression, Subgroup Analysis, and
Panel Data

Elastic Net Penalized Maximum Likelihood for Structural Equation
Models with Network GPT Framework
R package sparseSEM version 4.1

Forecasting and Early Outbreak Detection for Sparse Count Data

Sparse Truncated Singular Value Decomposition (from 'SVDLIBC')

Solution Paths of Sparse High-Dimensional Support Vector Machine
with Lasso or Elastic-Net Regularization
R package sparseSVM version 1.1-7

Spike-and-Slab Variational Bayes for Linear and Logistic
Regression

Sparse Vector Field Consensus for Vector Field Learning

Statistical Pattern Recognition and daTing using Archaeological
Artefacts assemblageS
R package SPARTAAS version 1.2.4

Variance Identification in Sparse Factor Analysis

Study Planning and Adaptation of Sample Size

Spatio-Temporal Modeling of Large Data Using a Spectral SPDE
Approach
R package spate version 1.7.5

Generalized Spatial Autoregresive Models for Mean and Variance