Yu *_*eng 21 warnings r matrix multidimensional-array correlation
我有一个流量数据矢量(29个数据)和一个3D矩阵数据(360*180*29)
我想找到单个矢量和3D矢量之间的相关性.相关矩阵的大小为360*180.
> str(ScottsCk_flow_1981_2010_JJA)
num [1:29] 0.151 0.644 0.996 0.658 1.702 ...
> str(ssta_winter)
num [1:360, 1:180, 1:29] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ...
> summary(ssta_winter)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
-2.8 -0.2 0.1 0.2 0.6 6.0 596849.0
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以上是矢量和3D矩阵的结构.3D矩阵有许多值为Null.
> for (i in 1:360) {
+ for(j in 1:180){
+ cor_ScottsCk_SF_SST_JJA[i,j] = cor(ScottsCk_flow_1981_2010_JJA,ssta_winter[i,j,])
+ }
+ }
There were 50 or more warnings (use warnings() to see the first 50)
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上面这部分代码是找到相关性的代码.但它提供了警告
> warnings()
Warning messages:
1: In cor(ScottsCk_flow_1981_2010_JJA, ssta_winter[i, j, ... :
the standard deviation is zero
2: In cor(ScottsCk_flow_1981_2010_JJA, ssta_winter[i, j, ... :
the standard deviation is zero
3: In cor(ScottsCk_flow_1981_2010_JJA, ssta_winter[i, j, ... :
the standard deviation is zero
4: In cor(ScottsCk_flow_1981_2010_JJA, ssta_winter[i, j, ... :
the standard deviation is zero
5: In cor(ScottsCk_flow_1981_2010_JJA, ssta_winter[i, j, ... :
the standard deviation is zero
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此外,相关矩阵的结果全为NULL.这怎么发生的?
> str(cor_ScottsCk_SF_SST_JJA)
num [1:360, 1:180] NA NA NA NA NA NA NA NA NA NA ...
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我使用完全相同的代码bfr与350流向量和360*180*350矩阵.这段代码完美无缺.
Jos*_*ien 20
一些想法.
首先,通过使用apply(),您可以使用以下内容替换该嵌套循环:
cor_ScottsCk_SF_SST_JJA <-
apply(ssta_winter, MARGIN = 1:2, FUN = cor, ScottsCk_flow_1981_2010_JJA)
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其次,看起来> 31%(596849/(360*180*29))的点ssta_winter是NaN或(可能)NA_real_.给定在包含单个向量的向量上计算的相关性的返回值NaN,
cor(c(1:3, NaN), c(1:4))
# [1] NA
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是不是所有那些NaNs都可能被s cor_ScottsCk_SF_SST_JJA填充NA?
第三,正如警告信息明确告诉你的那样,你传递给的一些矢量的cor()方差为零.它们与NaNs 无关:如下所示,当NaN涉及到R时,R不会抱怨0的标准偏差.(非常合理,因为您无法计算未定义数字的标准偏差):
cor(c(NaN, NaN, NaN, NaN), c(1,1,1,1))
# [1] NA
cor(c(1,1,1,1), c(1,2,3,4))
# [1] NA
# Warning message:
# In cor(c(1, 1, 1, 1), c(1, 2, 3, 4)) : the standard deviation is zero
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