[R] grouping data

Hi R-list, I have a data set with plot locations and observations and want to label them based on locations. For example, I have GPS information (x and y) as follows: > x [1] -87.85092 -87.85092 -87.85092 -87.85093 -87.85093 -87.85093 -87.85094 [8] -87.85094 -87.85094 -87.85096 -87.85095 -87

[R] Fwd: helps in data analysis

or suggestions, I would appreciate that. Please let me know if there is lack of information you may need before comments. Thank you very much in advance!! Steve Hong [[alternative HTML version deleted]] __ R-help@r-project.org mailing list htt

[R] AIC vs. extractAIC

Dear list, I am confused about two functions in R: AIC(fm) and extractAIC(fm). What is the difference between two and when do I have to use one over the other? I have found the similar question previously and still not clear for me to understand. I also looked at '?AIC' and '?extractAIC' in R,

[R] re-code missing value

Dear all, I have partial data set with four colums. First column is "site" with three factors (i.e., A, B, and C). From second to fourth columns (v1 ~ v3) are my observations. In the observations of the data set, "." indicates missing value. I replaced "." with NA. To replace "." with NA, I u

[R] Simulation code error

I guess I got error message since there are some observations without neighborhoods in the process of determining neighborhood structure randomly. Is there any way to ignore neighborhood structures with observations without neighborhoods and proceed the code? Thank you in advance!! Steve Hong

[R] Error in simulation R-code

ume grains 1690 1 170 0 1 1711 1 1930 0 2170 0 Thank you in advance!! Steve Hong [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/m

[R] Error in simulation R-code

0 2170 10 0 000 0 0 0 01 1 0 0 0 0 0 0 0 o.legume grains 1690 1 170 0 1 1711 1 1930 0 2170 0 Thank you in advance!! Steve Hong

[R] Add ID numbers on a plot

Dear List, I have (for example) 50 observations collected from 50 experimental sites and want to look at changes of 50 observations as function of time in a graph. I found that I could do that using R-code below: time2 <- 1:25 y1=rnorm(25, mean=0, sd=1) y2=rnorm(25, mean=0, sd=1) ... y50=rnorm