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计算R中数据集的多重方差

[英]Computing multiple variance of a dataset in R

My problem is somewhat related to this question. 我的问题与这个问题有关。

I have a data as below 我有如下数据

V1   V2
..   1
..   2
..   1
..   3

I need to calculate variance of data in V1 for each value of V2 cumulatively (This means that for a particular value of V2 say n ,all the rows of V1 having corresponding V2 less than n need to be included. 我需要针对V2每个值累计计算V1的数据方差(这意味着,对于V2的特定值,请说n ,必须包括V1对应的所有V2小于n所有行。

Will ddply help in such a case? ddply在这种情况下会ddply帮助吗?

I don't think ddply will help since it is built on the concept of taking non-overlapping subsets of a data frame. 我认为ddply不会有所帮助,因为它建立在采用数据帧的非重叠子集的概念上。

d <- data.frame(V1=runif(1000),V2=sample(1:10,size=1000,replace=TRUE))
u <- sort(unique(d$V2))
ans <- sapply(u,function(x) {
    with(d,var(V1[V2<=x]))
})
names(ans) <- u

I don't know if there's a more efficient way to do this ... 我不知道是否有更有效的方法来做到这一点...

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