对 R 中向量的不同元素应用不同的函数 [英] apply different functions to different elements of a vector in R

问题描述

申请很容易，但这对我来说是一个简而言之:

apply is easy, but this is a nutshell for me to crack:

在多参数回归中，优化器用于找到参数函数的最佳拟合，例如 x1,x2 数据.通常，如果优化器尝试优化转换参数(例如，使用 R 优化器，如 DEoptim、nls.lm)，并且特定于函数的优化器会更快根据我的经验，对来自一个参数函数的不同参数进行不同变换会更好.

In multi-parametric regression, optimisers are used to find a best fit of a parametric function to say x1,x2 Data. Often, and function specific, optimisers can be faster if they try to optimise transformed parameters (e.g. with R optimisers such as DEoptim, nls.lm) From experience I know, that different transformations for different parameters from one parametric function is even better.

我希望将 x.trans 中的不同函数(参见下文)应用于 x.val 中不同但在其位置对应的元素:

I wish to apply different functions in x.trans (c.f. below) to different but in their position corresponding elements in x.val:

可以使用的模拟示例.

#initialise
x.val <- rep(100,5);      EDIT: ignore this part ==>  names(x.val) <- x.names
x.select <- c(1,0,0,1,1)
x.trans <- c(log10(x),exp(x),log10(x),x^2,1/x)

#select required elements, and corresponding names
x.val = subset(x.val, x.select == 1)
x.trans = subset(x.trans, x.select == 1)

# How I tried: apply function in x.trans[i] to x.val[i]
...

有什么想法吗?(我尝试过 apply 和 sapply 但无法获取存储在 x.trans 中的函数)

Any ideas? (I have tried with apply, and sapply but can't get at the functions stored in x.trans)

推荐答案

你必须改用这个:

x.trans <- c(log10,exp,log10,function(x)x^2,function(x)1/x)

那么:

mapply(function(f, x) f(x), x.trans, x.val)

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