Question

我希望使用optim最小化函数，如下所示：

yield <- function(data, par) {
  with(data, par[1] + (par[2] + par[3]/par[4])*(1-exp(-par[4]*maturity))/(par[4]*maturity) - (par[3]*exp(-par[4]*maturity)/par[4]))
}
min.RSS <- function(data, par) {
  sum((data$price - 100*exp(-data$maturity*yield(data, par)))^2)
}
result <- optim(par = theta, min.RSS, data = data))

参数par[1]和par[4]必须是非负数，而其他两个不受约束。是否可以在optim函数中包含这些约束？

由于

Answer 1

让@BondedDust的建议非常明确：

yield <- function(data, par) {
  with(data, par[1] + (par[2] + par[3]/par[4])*(1-exp(-par[4]*maturity))/(par[4]*maturity) - (par[3]*exp(-par[4]*maturity)/par[4]))
}

# the function being optimized
min.RSS <- function(data, par) {

  # EXPONENETIATE PARAMTERS 1 AND 4 TO MAKE THEM POSITIVE.
  par[1] <- exp(par[1])
  par[4] <- exp(par[4])

  sum((data$price - 100*exp(-data$maturity*yield(data, par)))^2)

}


PAR <- theta

# LOG TRANSFRORM THE INITIAL VALUES FOR PARAMTERS 1 AND 4
PAR[1] <- log(PAR[1])
PAR[4] <- log(PAR[4])

# CALL optim()
result <- optim(par = PAR,
                min.RSS,
                data = data))


# THE BEST SET OF PARAMETERS
par <- result$par
# again, exponenetiate paramters 1 and 4 to make them positive.
par[1] <- log(par[1])
par[4] <- log(par[4])

R optim功能 - 设置各个参数的约束

1 个答案: