Question

此问题需要DEoptim个包：

install.packages("DEoptim")
library(DEoptim)

来自help(DEoptim)

Rosenbrock <- function(x){
x1 <- x[1]
x2 <- x[2]
100 * (x2 - x1 * x1)^2 + (1 - x1)^2
}

lower <- c(-10,-10)
upper <- -lower

## run DEoptim and set a seed first for replicability
set.seed(1234)
DEoptim(Rosenbrock, lower, upper)

现在这很好用：但是，如果我使用Npop

提供初始人口dim(Npop)[1] < 10*length(lower)

xini <- cbind(runif(10),runif(10))
ran <- abs(lower - upper)
Npop <- apply(xini,2,function(x) x*ran+lower)
DEoptim(Rosenbrock, lower, upper,DEoptim.control(initialpop = Npop))

我收到以下错误：

Error in DEoptim(Rosenbrock, lower, upper, DEoptim.control(initialpop = Npop)) : 
Initial population is not a matrix with dim. NP x length(upper).

我该怎么做？

与此问题相关：R DEoptim() function: How to select parameters to be opimised?

例如不估计1个参数，我不需要考虑它 DEoptim.control(initialpop)

Answer 1

这是我从DEoptim()

的作者那里得到的解决方法

library(DEoptim)

#From help(DEoptim)

Rosenbrock <- function(x){
          x1 <- x[1]
          x2 <- x[2]
          100 * (x2 - x1 * x1)^2 + (1 - x1)^2
}

lower <- c(-10,-10)
upper <- -lower

## run DEoptim and set a seed first for replicability

set.seed(1234)
DEoptim(Rosenbrock, lower, upper)

n <- length(lower) * 10 
# n <- length(lower) * 5 

xini <- cbind(runif(n),runif(n))
ran <- upper - lower
Npop <- as.matrix(apply(xini,2,function(x) x*ran+lower))
DEoptim(Rosenbrock, lower, upper, DEoptim.control(NP=n,initialpop = Npop))

Answer 2

关于上面的答案，apply函数似乎没有给出正确的矩阵。我相信您需要按行（1）应用然后转置矩阵。

Npop <- t(as.matrix(apply(xini,1,function(x) x*ran+lower)))

R DEoptim（）函数：如何使用比Npop更小的初始种群数

2 个答案: