Disciplined Convex Programming in R using 'Convex.jl'

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Documentation for package ‘convexjlr’ version 0.8.1

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addConstraint Add constraints to optimization problem
convex_setup Doing the setup for the package convexjlr
cvx_optim Solve optimization problem
dot Inner product
dotsort Inner product of two vectors after sorted
entropy sum(-x * log(x))
evaluate Get values of expressions at optimizer
Expr Create expressions to be used for optimization problem creation
geomean Geometric mean of x and y
huber Huber loss
J Make a variable to be of Julia's awareness
lambdamax Largest eigenvalues of x
lambdamin Smallest eigenvalues of x
logdet Log of determinant of x
logisticloss log(1 + exp(x))
logsumexp log(sum(exp(x)))
matrixfrac x^T P^-1 x
maximize Create optimization problem
maximum Largest elements
minimize Create optimization problem
minimum Smallest elements
neg Negative parts
norm p-norm of x
nuclearnorm Sum of singular values of x
operatornorm Largest singular value of x
optval Get properties of optimization problem
pos Positive parts
problem_creating Create optimization problem
property Get properties of optimization problem
quadform x^T P x
satisfy Create optimization problem
Semidefinite Create variable for optimization problem
square Square of x
status Get properties of optimization problem
sumlargest Sum of the largest elements
sumsmallest Sum of the smallest elements
sumsquares Sum of squares of x
tr Trace of matrix
value Get values of expressions at optimizer
Variable Create variable for optimization problem
variable_creating Create variable for optimization problem
vec Vector representation
vecdot Inner product of vector representation of two matrices
vecnorm p-norm of vector representation of x