[R] D'agostino-Pearson K2 omnibus test.

Hi, Is there an implementation of the D'agostino K2 omnibus test in an R package. I've found the D test in the fBasics package, but this doesn't give the same answer as my algorithm. I've already coded a version of the K2 and need to check the results. I have a set of spectra with gaussian

[R] Fisher's exact test

Hi, I'm trying to run Fisher's Exact test on the data below, but I'm not sure how interpret the data shown. Can someone tell me what this is saying? Looking at the numbers it should be that there's no significant difference between the HDL and LDL, but a p-value of 1 seems high. Is the low value

[R] Hartigan's Dip test

Hi, I just got a value for the dip test out of my data of 0.074 for a sample size of 33. I'm trying to work out what this actually means though? Could someone help me relate this to a p-value? Thanks James __ R-help@r-project.org mailing list

[R] Rcorr

Hi, I've just run an rcorr on some data in Spearman's mode and it's just produced the following values; [,1] [,2] [1,] 1.00 -0.55 [2,] -0.55 1.00 n= 46 P [,1] [,2] [1,] 0 [2,] 0 I presume this means the p-value is lower than 0.5, but is there any way of increasing the

Re: [R] Rcorr

No, that's made no difference, sorry. Frank E Harrell Jr wrote: James Allsopp wrote: Hi, I've just run an rcorr on some data in Spearman's mode and it's just produced the following values; [,1] [,2] [1,] 1.00 -0.55 [2,] -0.55 1.00 n= 46 P [,1] [,2] [1,] 0 [2

Re: [R] Linear least squares fit with errors in both x and y values.

James Allsopp jamesaalls...@go oglemail.com

[R] Linear least squares fit with errors in both x and y values.

Hi, I'd like to perform a weighted linear least squares fit with R on data with varying errors on both vectors. I can do this with one axis using lm, but have no idea where to go from here. I've tried googling, but no idea. Any suggestions? I'm also trying to plot these errors on a graph. Again I

[R] Linear least squares fit with errors in both x and y values.

HI, I'd like to perform a weighted linear least squares fit with R on data with varying errors on both vectors. I can do this with one axis using lm, but have no idea where to go from here. I've tried googling, but no idea. Any suggestions? Thanks, James