我有一个与数据集一起使用的代码。我发现它不想使用LN（x）功能。可以找到数据集在这里。
LY <- ln(Apple$Close - Apple$Open)
log（x）中的警告：nans产生
Could you please help me to fix this problem?
I've got a code that works with the Data Set. I found out that it doesn't want to work with the ln(x) function. The data set can be found here.
LY <- ln(Apple$Close - Apple$Open)
Warning in log(x) : NaNs produced
Could you please help me to fix this problem?
发布评论
评论（2）
由于股票可能上涨也可能下跌（不幸的是），
收盘价可能小于开盘价，并且收盘价 - 开盘价可能为负值。取负数的自然对数是没有意义的；这就像除以零，或者更准确地说，就像取负数的平方根。实际上，您可以取具有负实部的复数的对数：
...但是“i乘以pi”对于进一步的数据可能不是一个非常有用的结果分析...
（在 R 中，
log()取自然对数。虽然SciViews包提供ln()作为同义词，但您可以不妨习惯使用log()- 这是大多数编程语言的约定...）根据您想要执行的操作，关闭/打开比率的对数可以是有用的值 (
log(Close/Open))：当CloseClose，时，此值为负。开盘收盘>时为正打开）。正如 @jpiversen 指出的，这称为对数回报；正如 @KarelZe 指出的，log(Close/Open)在数学上相当于log(Close) - log(Open)（这可能是你的教授想要的...... ？？？）Since stocks can go down as well as up (unfortunately),
Closecan be less thanOpenandClose - Opencan be negative. It just doesn't make sense to take the natural log of a negative number; it's like dividing by zero, or more precisely like taking the square root of a negative number.Actually, you can take the logarithm of a complex number with a negative real part:
... but "i times pi" is probably not a very useful result for further data analysis ...
(in R,
log()takes the natural logarithm. While theSciViewspackage providesln()as a synonym, you might as well just get used to usinglog()- this is a convention across most programming languages ...)Depending on what you're trying to do, the logarithm of the close/open ratio can be a useful value (
log(Close/Open)): this is negative whenClose < Open, positive whenClose > Open). As @jpiversen points out, this is called the logarithmic return; as @KarelZe points out,log(Close/Open)is mathematically equivalent tolog(Close) - log(Open)(which might be what your professor wanted ... ???)您在寻找对数回报吗？在这种情况下，公式为：
由于两个正值的
A / B始终为正，因此不会创建NaN。Are you looking for logarithmic return? In that case the formula would be:
Since
A / Bfor two positive values is always positive, this will not createNaNs.