【发布时间】:2015-02-08 22:14:49
【问题描述】:
我需要更新函数内的模型公式。这是一个例子:
A <- runif(n = 200) # generate some data
B <- runif(n = 200)
P <- 1/(1+exp(.5-A)) # generate event probability
outcome <- runif(n = 200) < P # generate outcome
my.function <- function(model, data.to.add) { # this is the function for updating the formula
new.model <- update(object = model, formula. = ~ . + data.to.add)
return (new.model)
}
test <- my.function(model = glm(outcome ~ B, family = binomial(link="logit")), data.to.add = A)
不幸的是,执行此代码会引发如下错误:
Error in eval(expr, envir, enclos) : object 'data.to.add' not found
似乎my.function 无法将变量data.to.add 的值提供给update 函数。我可以做些什么来为另一个函数中的update 函数提供正确的变量范围?
编辑:好的,如果要传递给要更新的函数的变量在全局环境中,那么您的解决方案很好,现在如果我必须在函数内定义变量,由于范围有限,我再次遇到错误变量:
A <- runif(n = 200) # generate some data
P <- 1/(1+exp(.5-A)) # generate event probability
outcome <- runif(n = 200) < P # generate outcome
nested.update<-function(model) {
B<-runif(n = 200)
my.function <- function(model, data.to.add) { # this is the function for updating the formula
data.to.add <- paste('. ~ . +', deparse(substitute(data.to.add)), sep = "")
new.model <- update(object = model, formula. = data.to.add)
return (new.model)
}
return(my.function(model = model, data.to.add = B))
}
nested.update(model = glm(outcome ~ A, family = binomial(link="logit")))
【问题讨论】: