更多的MLE麻烦 [英] More MLE troubles

问题描述

我处于学生研究职位，并且是R的新手.我曾问过类似的问题(发布在这里:

I am in a student research position and am new to R. I have asked a question similar (posted here:MLE Issues). I have resolved the initial problem but i have encountered more problems with this function.

我仍在使用此函数尝试估算theta [i]， 当前每个其他变量都已知的位置.

I am still using this function for trying to estimate theta[i], where each of the other variables is currently known.

下面是我的代码:

  maxParam <- function(theta) {
    logl <- sum(for (i in 1:length(doses)) {
      sum(
        for (j in 1:LITTERS.M) {
          sum(
            for (k in 0:(litterResponses[i,j]-1)) {
              sum(log10(probabilityResponses[i] + k * theta[i]))
            }
            +
            for (k in 0:(litterSizes[i,j]-litterResponses[i,j]-1)) {
              sum(log10(1 - probabilityResponses[i] + k * theta[i]))
            }
            -
            for (k in 0:(litterSizes[i,j] - 1)) {
              sum(log10(1 + k * theta[i]))
            }
          )
        }
      )
    })

    return (-logl)
  }

  mle.fit <- mle(maxParam, start=list(theta=c(1,1,1,1,1,1)))
  print(mle.fit)

我被抛出的错误是:

错误:缺少参数"theta"，没有默认值

Error: argument "theta" is missing, with no default

如果错误很傻，我对此表示歉意，对R的了解却很少.

I apologize if the error is silly, I have little knowledge of R.

注释: 我正在使用(1,1,1,1,1,1,1)的向量作为theta的检验.它不是实际数据.剂量是6的向量，对应于血清的剂量水平.凋落物响应是一个矩阵，描述了每窝每剂对血清的响应. LitterSizes是一个矩阵，描述每窝每剂的一窝产仔数. LITTERS.M是与血清接触的垫料的初始数量. ProbabilityResponses是一个向量，它描述了给定小鼠受到血清影响的可能性.

Notes: I am using a vector of (1,1,1,1,1,1) as a test for theta. It is not actual data. Doses is a vector of 6 that corresponds to dose levels of a serum. Litter Responses is a matrix that describes the responses to the serum per dose per litter. LitterSizes is a matrix that describes the size of a litter per dose per litter. LITTERS.M is the initial number of litters that came in contact with serum. ProbabilityResponses is a vector that describes the probability that a given mouse will be affected by the serum.

推荐答案

函数mle不接受初始起始值的向量.要通过优化找到的每个参数都需要作为标量传递.将函数的声明更改为:

The function mle does not accept a vector of initial starting values. Each parameter to be found by optimisation needs to be passed as a scalar. It is sufficient to change the declaration of your function to:

maxParam <- function(theta_1 = 1, theta_2 = 1, etc) {
    theta <- unlist(as.list(environment()))

    ... # rest of function follows
  }

其中，etc表示根据需要将其替换为theta_3 = 1，theta_4 = 1.函数mle然后可以通过以下方式调用:

where etc means replace this with theta_3 = 1, theta_4 = 1 as necessary. The function mle can then be called with:

mle.fit <- mle(maxParam)

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