correlation failure - Pearson

I want to write to datafile information about correlation as follows:

*korelacja=cor(p2,d2,method="pearson",use = "complete.obs")
korelacja2=cor(p2,d2,method="kendall",use = "complete.obs")
korelacja3=cor(p2,d2,method="spearman",use = "complete.obs")
dane=paste(korelacja,korela开发者_JS百科cja2,korelacja3,sep=';')
write(dane,file=nazwa,append=TRUE)*

Results are strange for me - Pearson correlation is very high (always equal one), but Kendall and Spearman is very low. I create scatterplots and I don't see linear correlation.

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It's not hard to replicate this pattern if you have some large outliers in your data that dominate the Pearson correlation but are relatively insignificant in the non-parametric (Kendall/Spearman) approaches. For example, here's a concocted data set with nothing going on except for one large outlier:

> set.seed(1001)
> x <- c(runif(1000),1e5)
> y <- c(runif(1000),1e5)
> cor(x,y,method="pearson")
[1] 1
> cor(x,y,method="kendall")
[1] -0.02216583
> cor(x,y,method="spearman")
[1] -0.03335352

This is consistent with your description so far, although you ought in this case to be able to see the outliers in your scatterplots ...