CVXR: Disciplined Convex Optimization

Canonical link: https://rscholar.com/pkg/CVXR

Anqi Fu • Balasubramanian Narasimhan • David W Kang • Steven Diamond • John Miller • Stephen Boyd • Paul Kunsberg Rosenfield • View description and downloads View dependencies GitHub project

2017 Published

1.0-15 Version

0 Citations

7 Authors

Referenced by ⇅	Year
CopSens: Copula-Based Sensitivity Analysis for Observational Causal Inference (Version 0.1.0)	2022
DebiasInfer: Efficient Inference on High-Dimensional Linear Model with Missing Outcomes (Version 0.2)	2023
DiSCos: Distributional Synthetic Controls Estimation (Version 0.1.1)	2024
EpiForsk: Code Sharing at the Department of Epidemiological Research at Statens Serum Institut (Version 0.1.1)	2023
GhostKnockoff: The Knockoff Inference Using Summary Statistics (Version 0.1.0)	2021
HonestDiD: Robust Inference in Difference-in-Differences and Event Study Designs (Version 0.2.6)	2024
LavaCvxr: Lava Estimation for the Sum of Sparse and Dense Signals(3 Methods) (Version 1.0.2)	2021
MaximinInfer: Inference for Maximin Effects in High-Dimensional Settings (Version 2.0.0)	2021
PlackettLuce: Plackett-Luce Models for Rankings (Version 0.4.3)	2017
PlaneGeometry: Plane Geometry (Version 1.6.0)	2020
PortfolioAnalytics: Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios (Version 2.0.0)	2015
Rdimtools: Dimension Reduction and Estimation Methods (Version 1.1.2)	2017
Riemann: Learning with Data on Riemannian Manifolds (Version 0.1.4)	2020
RobustIV: Robust Instrumental Variable Methods in Linear Models (Version 0.2.5)	2022
SIHR: Statistical Inference in High Dimensional Regression (Version 2.1.0)	2021
SLSEdesign: Optimal Regression Design under the Second-Order Least Squares Estimator (Version 0.0.3)	2024
T4transport: Tools for Computational Optimal Transport (Version 0.1.2)	2020
WRI: Wasserstein Regression and Inference (Version 0.2.0)	2020
cuadramelo: Matrix Balancing and Rounding (Version 1.0.0)	2024
ecpc: Flexible Co-Data Learning for High-Dimensional Prediction (Version 3.1.1)	2021
fairml: Fair Models in Machine Learning (Version 0.8)	2020
filling: Matrix Completion, Imputation, and Inpainting Methods (Version 0.2.3)	2017
finbipartite: Learning Bipartite Graphs: Heavy Tails and Multiple Components (Version 0.1.0)	2023
fungible: Psychometric Functions from the Waller Lab (Version 2.4.4)	2015
glmmrOptim: Approximate Optimal Experimental Designs Using Generalised Linear Mixed Models (Version 0.3.5)	2023
graphicalExtremes: Statistical Methodology for Graphical Extreme Value Models (Version 0.3.2)	2019
hedgedrf: An Implementation of the Hedged Random Forest Algorithm (Version 0.0.1)	2024
kantorovich: Kantorovich Distance Between Probability Measures (Version 3.2.0)	2016
portfolioBacktest: Automated Backtesting of Portfolios over Multiple Datasets (Version 0.4.1)	2019
scpi: Prediction Intervals for Synthetic Control Methods with Multiple Treated Units and Staggered Adoption (Version 2.2.5)	2022
spBPS: Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning (Version 0.0-4)	2024
spStack: Bayesian Geostatistics Using Predictive Stacking (Version 1.0.1)	2024
spectralGraphTopology: Learning Graphs from Data via Spectral Constraints (Version 0.2.3)	2019
starnet: Stacked Elastic Net (Version 0.0.7)	2020
tramnet: Penalized Transformation Models (Version 0.0-8)	2020
transreg: Penalised Regression with Multiple Sets of Prior Effects ('Transfer Learning') (Version 1.0.3)	2023
wdnet: Weighted and Directed Networks (Version 1.2.3)	2022

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.