我试图用R中的optim（）函数复制multinom（）函数的结果，但它不会产生相同的结果。怎么了？

我想用R中的optim（）函数复制multinom（）函数的结果，但它不会产生相同的结果。怎么了

首先，我将一个公共数据导入为“ml”

从执行多项逻辑回归的multinom（）函数中获取结果的代码，结果如下：

with(ml, table(ses,prog))
with(ml, do.call(rbind,tapply(write, prog, function(x) c(M = mean(x), SD = sd(x)))))

library(nnet)
ml$prog2 <- relevel(ml$prog, ref = "academic")
ml_pckg <- multinom(prog2 ~ write + ses, data = ml)
summary(ml_pckg)

z <- summary(ml_pckg)$coefficients/summary(ml_pckg)$standard.errors
z

$par
[1]  0.05325004 -0.01417267 -0.64375499 -0.96137147  6.33471560 -0.86154161  0.92387035 -0.65728823

$value
[1] 103.7692

$counts
function gradient 
     353       NA 

$convergence
[1] 0

$message
NULL

获取z统计信息的代码和结果如下：

with(ml, table(ses,prog))
with(ml, do.call(rbind,tapply(write, prog, function(x) c(M = mean(x), SD = sd(x)))))

library(nnet)
ml$prog2 <- relevel(ml$prog, ref = "academic")
ml_pckg <- multinom(prog2 ~ write + ses, data = ml)
summary(ml_pckg)

z <- summary(ml_pckg)$coefficients/summary(ml_pckg)$standard.errors
z

$par
[1]  0.05325004 -0.01417267 -0.64375499 -0.96137147  6.33471560 -0.86154161  0.92387035 -0.65728823

$value
[1] 103.7692

$counts
function gradient 
     353       NA 

$convergence
[1] 0

$message
NULL

接下来，我编写了复制上述结果的代码。 我为分类相关/独立变量生成了虚拟变量，如下所示：

ml$prog_academic <- ifelse(ml$prog == "academic", 1, 0)
ml$prog_general <- ifelse(ml$prog == "general", 1, 0)
ml$prog_vocational <- ifelse(ml$prog == "vocational", 1, 0)

ml$ses_low <- ifelse(ml$ses == "low", 1, 0)
ml$ses_middle <- ifelse(ml$ses == "middle", 1, 0)
ml$ses_high <- ifelse(ml$ses == "high", 1, 0)

2.852198 -0.0579287 -0.5332810 -1.1628226  5.218260 -0.1136037  0.2913859 -0.9826649

如果结果与mlogit（）函数的结果一致，$par应如下所示：

ml$prog_academic <- ifelse(ml$prog == "academic", 1, 0)
ml$prog_general <- ifelse(ml$prog == "general", 1, 0)
ml$prog_vocational <- ifelse(ml$prog == "vocational", 1, 0)

ml$ses_low <- ifelse(ml$ses == "low", 1, 0)
ml$ses_middle <- ifelse(ml$ses == "middle", 1, 0)
ml$ses_high <- ifelse(ml$ses == "high", 1, 0)

2.852198 -0.0579287 -0.5332810 -1.1628226  5.218260 -0.1136037  0.2913859 -0.9826649

我一次又一次地检查我的代码和似然函数，但在这里没有发现任何错误。我想可能是初始参数设置错误，或者我创建的函数有问题

有谁能给我一些建议来解决这个问题吗

谢谢大家!

mlogit <- function(B){
  B <- matrix(B, nrow=2, ncol=4, byrow=T) 
  for (i in 1:nrow(xb)){  #i is the dimension of individual: 200
    for (j in 1:ncol(xb)){  #j is the dimension of dependant variables -1 (categorical): 2
      xb[i,j] <- sum(X[i,]*B[j,]) #200*2
    }
  }
  
  exp <- exp(xb) #200*2
  sumexp <- rowSums(exp) #200*1
  sumexp <- as.numeric(sumexp)
  
  yxb <- Y*xb #200*2
  sumyxb <- sum(yxb)
  
  ll <-  sumyxb-sum(log(1+sumexp))
  -ll
}

mlogit_result <- optim(par = B_0, fn = mlogit)
mlogit_result

$par
[1]  0.05325004 -0.01417267 -0.64375499 -0.96137147  6.33471560 -0.86154161  0.92387035 -0.65728823

$value
[1] 103.7692

$counts
function gradient 
     353       NA 

$convergence
[1] 0

$message
NULL

2.852198 -0.0579287 -0.5332810 -1.1628226  5.218260 -0.1136037  0.2913859 -0.9826649