[英]sapply or other apply function in R
I wrote some code yesterday and it was confusing you to help. 昨天我写了一些代码,这使您困惑。 Sorry about that.
对于那个很抱歉。 So I wrote it again in an easier way.
所以我以一种更简单的方式再次写了它。
My question is: is there easier (or faster) way to implement the following code? 我的问题是:有没有更简单(或更快速)的方法来实现以下代码?
k <- c(.04, .08, .12, .16, .2);
library(plyr)
valfcn <- function(k, V_next){
a <- .3;
b <- .6;
return_val <- vector()
for(i in 1:5){
tmp <- vector()
for(j in 1:5){
tmp[j] <- (log(k[i]^a - k[j]) + b*V_next[j]);
}
return_val <- c(return_val,max(tmp[i]))
}
return_val
}
V0 <- c(rep(0,5))
V1 <- valfcn(k,V0)
V2 <- valfcn(k,V1)
V1
V2
I'd like to use alternative way which might be shorter but faster, instead of using the for-loop method. 我想使用替代方法,它可能更短但更快,而不是使用for循环方法。
Best! 最好!
I believe the sapply()
isn't necessary based on your description. 我相信
sapply()
根据您的描述不是必需的。 Something like this might do what you're looking for: 这样的事情可能会满足您的需求:
valfcn <- function(k, V_next){
a <- .3;
b <- .6;
max(log(k^a - k) + b*V_next);
}
In this version, the transformation being done to k
produces a vector and then max()
operates on the entire vector. 在此版本中,对
k
进行的转换将生成一个向量,然后max()
对整个向量进行运算。 No need to use a loop or use sapply()
, since max()
takes care of it. 不需要使用循环或使用
sapply()
,因为max()
会处理它。
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