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convexjlr  

Disciplined Convex Programming in R using "Convex.jl"
View on CRAN: Click here


Download and install convexjlr package within the R console
Install from CRAN:
install.packages("convexjlr")

Install from Github:
library("remotes")
install_github("cran/convexjlr")

Install by package version:
library("remotes")
install_version("convexjlr", "0.8.1")



Attach the package and use:
library("convexjlr")
Maintained by
Changcheng Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-20
Latest Update: 2023-08-19
Description:
Provides a simple high-level wrapper forJulia package Convex.jl see httpsgithub.comJuliaOptConvex.jl formore informationwhich makes it easy to describe and solve convex optimization problems in R.The problems can be dealt with includelinear programssecond-order cone programssemidefinite programsexponential cone programs.
How to cite:
Changcheng Li (2017). convexjlr: Disciplined Convex Programming in R using "Convex.jl". R package version 0.8.1, https://cran.r-project.org/web/packages/convexjlr. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.5.0 (2017-06-20 00:32), 0.5.1 (2017-06-21 21:29), 0.6.1 (2017-10-01 23:27), 0.7.0 (2018-04-29 05:12), 0.8.1 (2018-12-16 22:30)
Other packages that cited convexjlr R package
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Other R packages that convexjlr depends, imports, suggests or enhances
Functions, R codes and Examples using the convexjlr R package
Some associated functions: Expr . J . addConstraint . convex_setup . cvx_optim . dot . dotsort . entropy . geomean . huber . lambdamax . lambdamin . logdet . logisticloss . logsumexp . matrixfrac . maximum . minimum . neg . norm . nuclearnorm . operatornorm . pos . problem_creating . property . quadform . square . sumlargest . sumsmallest . sumsquares . tr . value . variable_creating . vec . vecdot . vecnorm . 
Some associated R codes: evaluate.R . expr.R . expression.R . first.R . operator.R . problem.R . variable.R .  Full convexjlr package functions and examples
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