[EMAIL PROTECTED] wrote:
Full_Name: Marek Ancukiewicz
Version: 1.8.1
OS: Linux
Submission from: (NULL) (132.183.12.87)
Function cor() incorrectly handles missing observation with method=spearman:
x - c(1,2,3,NA,5,6)
y - c(4,NA,2,5,1,3)
cor(x,y,use=complete.obs,method=s)
[1]
Dear Uwe,
You are wrong. First, I've read the help file before
submitting the report. For two variables,
use=pairwise.complete.obs and use=complete.obs should be
equivalent, shouldn't it? Of sourse, the results will be
different when we have more than 2 variables. Second, with the
call you
Marek Ancukiewicz wrote:
Dear Uwe,
You are wrong.
Whoops. My apologies!!!
In R-1.9.0 beta I get:
cor(x[!is.na(x)!is.na(y)],y[!is.na(x)!is.na(y)],method=s)
# [1] -0.4
cor(x,y,use=complete.obs, method=s)
# [1] -0.5291503
I'll take a look!
Uwe
First, I've read the help file before
On Fri, 9 Apr 2004 [EMAIL PROTECTED] wrote:
Dear Uwe,
You are wrong. First, I've read the help file before
submitting the report. For two variables,
use=pairwise.complete.obs and use=complete.obs should be
equivalent, shouldn't it? Of sourse, the results will be
different when we have
On Fri, 9 Apr 2004, Marek Ancukiewicz wrote:
Dear Thomas,
The question becomes: how do we rank missing values?
That's one of the questions. It's not the only question. Suppose x has
no missing values but y has a missing value. Should the ranks for x be
based on the whole vector or just on
