Question

我正在使用mlogit包进行多项逻辑回归。我想将弹性净罚分（Hastie和Zou，2005）添加到似然函数中。如：https://web.stanford.edu/~hastie/Papers/B67.2%20(2005)%20301-320%20Zou%20&%20Hastie.pdf

我已经尝试过glmnet包，但似乎它不像mlogit那样工作：它似乎不能识别长格式和不同选择集的数据。它以某种方式产生意想不到的结果。（它在mlogit中工作正常，但可能没有惩罚。）

我正在尝试更改包中的代码，mlogit.lnl.R文件似乎包含似然函数，我试图在mlogit.lnl.R文件中添加一个套索术语“lnl”，但是它产生了相同的结果，好像我没有添加它。

在mlogit.lnl.R文件中：

lnl.slogit <- function(param, X, y, weights = NULL, gradient = FALSE,
                    hessian = FALSE, opposite, direction = rep(0, length(param)),
                    initial.value = NULL,stptol = 1E-01){
  balanced <- FALSE
  step <- 2
  repeat{
    step <- step / 2
    if (step < stptol) break
    eXb <- lapply(X, function(x) exp(crossprod(t(x), param + step * direction)))
    seXb <- suml(eXb)
    P <- lapply(eXb, function(x){v <- x/seXb; v[is.na(v)] <- 0; as.vector(v)})
    Pch <- Reduce("+", mapply("*", P, y, SIMPLIFY = FALSE))
    lnl <- sum(opposite * weights * log(Pch)) 
    if (is.null(initial.value) || lnl <= initial.value) break
  }
  if (gradient | hessian) PX <- suml(mapply("*", X, P, SIMPLIFY = FALSE))
  if (gradient){
    Xch <- suml(mapply("*", X, y, SIMPLIFY = FALSE))
    gradi <-  opposite * weights * (Xch - PX)
    attr(lnl, "gradi") <- gradi
    attr(lnl, "gradient") <- if (is.matrix(gradi)) apply(gradi,2,sum) else 
sum(gradi)
  }
  if (hessian){
    XmPX <- lapply(X, function(x){g <- x - PX; g[is.na(g)] <- 0; g})
    hessian <-   - suml( mapply(function(x, y) crossprod(x * y, y),
                            P, XmPX, SIMPLIFY = FALSE))
    attr(lnl, "hessian") <- opposite * hessian
  }
  if (step < stptol) lnl <- NULL
  else{
    P <- Reduce("cbind", P)
    colnames(P) <- names(y)
    attr(lnl, "probabilities") <- P
    attr(lnl, "fitted") <- Pch
    attr(lnl, "step") <- step
  }
  lnl + 0.5*sum(abs(param)) #I added the lasso here, the shrinkage factor here is 0.5
                              #but eventually, i want the elastic net penalty
}

关于如何在mlogit包中添加惩罚词的任何想法？或者还有其他任何可以做我想要的套餐吗？

提前致谢。

PS：包的代码可在此处获取：https://github.com/cran/mlogit/tree/master/R

弹性网与mlogit

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