Question

我正在围绕lm构建一个包装器来进行一些额外的计算。我希望包装器将...传递给lm，但我遇到了lm的{{1}}参数问题。

weights

如果我用权重参数调用包装器，

LmWrapper <- function(df, fmla, ...) {
  est <- lm(fmla, df, ...)
  list(model = est)
}

R不知道在哪里寻找重量：

data(airquality)
LmWrapper(airquality, Ozone ~ Wind, weights = Temp)

Error in eval(expr, envir, enclos) : ..1 used in an incorrect context, no ... to look in帮助页面显示

所有lm，weights和subset的评估方式与offset中的变量相同，即formula中的变量，然后是data的环境。

但包装器似乎改变了一些东西。

我该如何解决这个问题？

上述错误的formula如下所示：

traceback()

直接致电8: eval(expr, envir, enclos) 7: eval(extras, data, env) 6: model.frame.default(formula = fmla, data = df, weights = ..1, drop.unused.levels = TRUE) 5: stats::model.frame(formula = fmla, data = df, weights = ..1, drop.unused.levels = TRUE) 4: eval(expr, envir, enclos) 3: eval(mf, parent.frame()) 2: lm(fmla, df, ...) at #2 1: LmWrapper(diamonds, price ~ carat, weights = depth)，效果很好：

lm

Answer 1

所以问题是lm通常在参数数据中查找这些名称，但某种方式确定了问题。您可以通过查找列引用并手动传递它来解决此问题。

LmWrapper <- function(df, fmla, ...) {
  # get names of stuff in ...
  argNames = sapply(substitute(list(...))[-1L], deparse)
  # look for identical names in df
  m = match(names(df), argNames, 0L)
  # store other arguments from ... in a list
  args = list(eval(parse(text = argNames[-m])))
  # name the list
  names(args) = names(argNames[-m])
  # store complete values in args, instead of just references to columns
  # the unlist code is rather ugly, the goal is to create a list where every
  # element is a column of interest
  args[names(argNames)[m]] = unlist(apply(df[, as.logical(m), drop = FALSE], 
                                       2, list), recursive = FALSE)
  # also put other stuff in there
  args$formula = fmla
  args$data = df
  # do lm
  est = do.call(lm, args)
  list(model = est)
}

data(airquality)

airquality$subset = airquality$Solar.R > 200
LmWrapper(airquality, Ozone ~ Wind, weights = Temp, subset = subset, 
          method = 'qr')

上面的代码不是最漂亮的，但它适用于subset和weights。或者，您可以将weights和subset作为例外处理。

Answer 2

感谢范德曼（Vandenman）的回答。我刚刚实现了两个共享的更改，以防其他人遇到此线程：

1）如果...中除了数据列之外没有参数，则上述代码在列表中创建一个NA元素，并引发警告-我在下面添加了一个条件来解决此问题。

2）上面代码返回的模型对象调用非常长，因为它包含每个权重等。如果您不关心使用update()的能力，那么替换它可能会更有见地通过实际的函数调用来记录发生的情况，如下所述。

run_lm <- function(df, formula, ...) {
    # get names of stuff in ...
    argNames = sapply(substitute(list(...))[-1L], deparse)
    # look for identical names in df
    m = match(names(df), argNames, 0L)

    # store other arguments from ... in a list, if any
    dot_args <- eval(parse(text = argNames[-m]))
    if (is.null(dot_args)) {args <- list()
    } else {
      args <- list(dot_args)
      # name the list
      names(args) = names(argNames[-m])
      }

    # store complete values in args, instead of just references to columns
    # the unlist code is rather ugly, the goal is to create a list where every
    # element is a column of interest
    args[names(argNames)[m]] = unlist(apply(df[, as.logical(m), drop = FALSE], 
                                            2, list), recursive = FALSE)
    # also put other stuff in there
    args$formula = formula
    args$data = df
    # do lm
   mod <- do.call(lm, args)
   mod$call <- sys.call()
   mod
   }

省略号麻烦：传递给lm

2 个答案: