您好我在rm(list=ls())
library(deSolve)
l <- 0.5 # bone 1/2 thickness (cm)
x_vec <- c(0.05, 0.15, 0.25, 0.30, 0.45)
A1meas <- c(0.51, 0.55, 0.64, 0.70, 0.92)
# x_vec <- -x_vec*l
l234 <- 2.8262e-6/(365.25*24*3600)
length_series <- 100
funmin <- function(x) {
A1_0 <- 0.025 # (238U) at the surface of the bone (disintegrations per second)
K <- x[1] # D/R diffusion coefficient/volumetric equilibirum constant
t <- x[2] # age in yr
t <- t*(365.25*24*3600)
series238 <- vector(mode="numeric", length=length_series+1)
A1calc <- vector(mode="numeric", length=length(x_vec))
i <- 0
for (x in x_vec){
for (n in 0:length_series){
series238[n+1] <- (-1)^n/(2*n + 1)*exp(-K*((2*n + 1)^2)*pi^2*t/(4*l^2))*cos((2*n + 1)/2*pi*x/l)
}
sum_series238 <- sum(series238)
i <- i+1
A1calc[i] <- A1_0*(1 - 4/pi*sum_series238)
}
fmin <- (A1calc - A1meas)^2
}
optim(c(1e-13, 1e4), funmin, method = "L-BFGS-B",
lower = c(1e-16, 1e3), upper = c(1e-8, 1e6))
函数中尝试最小化wreq，但我收到此错误消息：
optim中的错误（c（1e-13,10000），funmin，method =＆＃34; L-BFGS-B＆＃34;，lower = c（1e-16，：optim中的目标函数评估长度为5而不是1
任何想法我做错了什么？见下面的代码。
0.5答案 0 :(得分：0)
得到它......正如错误信息所说（呃！），评估的函数的长度为5而不是这个。
这有效：fmin <- sum((A1calc - A1meas)^2)