使用多参数F_objective函数在 R 中进行 ROI 优化

Question

试图在 R 中运行简单的 ROI 优化，但经过数小时的坐立不安，我不知所措。我不断收到错误：

Error in .check_function_for_sanity(F, n) : 
cannot evaluate function 'F' using 'n' = 5 parameters.

下面是示例代码：

library(ROI)
library(nloptr)
library(ROI.plugin.nloptr)
#Generate some random data for this example
set.seed(3142)
myRet = matrix(runif(100 * 5, -0.1, 0.1), ncol = 5)
myCovMatrix = cov(myRet)
myRet <- myRet
myCovMatrix <- myCovMatrix
# Sample weights
w <-  rep(1/ncol(myRet), ncol(myRet))
#Define functions for the optimisation
diversificationRatio = function(w, covMatrix)
{
weightedAvgVol = sum(w * sqrt(diag(covMatrix)))
portfolioVariance = (w %*% covMatrix %*% w)[1,1]
- 1 * weightedAvgVol / sqrt(portfolioVariance)
}
# Check that the F_objective function works:
diversificationRatio(w, myCovMatrix)
# Now construct the F_objective
foo <- F_objective(F = diversificationRatio, n = (ncol(myRet)))

关于传递给n多少个参数的任何想法？

Answer 1

F_objective需要一个只有一个参数的函数，所以你必须编写一个包装函数。

#Define functions for the optimisation
diversificationRatio <- function(w, covMatrix) {
weightedAvgVol <- sum(w * sqrt(diag(covMatrix)))
portfolioVariance <- (w %*% covMatrix %*% w)[1,1]
- 1 * weightedAvgVol / sqrt(portfolioVariance)
}
# Check that the F_objective function works:
wrapper <- function(x) diversificationRatio(x, myCovMatrix)
# Now construct the F_objective
o <- OP(F_objective(F = wrapper, n = (ncol(myRet))))
ROI_applicable_solvers(o)
start <- runif(ncol(myRet))
s <- ROI_solve(o, solver = "nloptr", start = start, method = "NLOPT_LD_SLSQP")
s
solution(s)