search for: byears

Hello, everybody, There is the first time for me to post a question, because I really cannot find answer from books, websites or my colleagues. Thank you in advance for your help! I am running likelihood ratio test to find if the simpler model is not significant from more complicated model. However, when I run LRT to compare them, the test did not return F value and p-value for me. What's the

I am a little bit confusing about the following help message on how to fit a GAM model with interaction between factor and smooth terms from http://rss.acs.unt.edu/Rdoc/library/mgcv/html/gam.models.html: ?Sometimes models of the form: E(y)=b0+f(x)z need to be estimated (where f is a smooth function, as usual.) The appropriate formula is: y~z+s(x,by=z) - the by argument ensures that the smooth

Dear R users, my dataframe looks like this head(dat) Id sex byear age 1 300 m 2003 50 2 300 m 2003 36 3 402 f 2003 29 4 402 f 2003 21 5 402 f 2003 64 6 150 m 2005 43 ... ...(where Id is just the Identification number of Individual, sex (male or female), byear (=birthyear)) now, I 'd like to add a column, where each Individual gets an automated number starting

hi, I have been trying to do this in R (have implemented it in Excel) but I have been using a very inefficent way (loops etc.). I have matrix A (columns are years and ages are rows) and matrix B (columns are birth yrs and rows are ages) I would like to first turn matrix A into matrix B And then I would like to convert matrix B back again to the original matrix A. (I have left out details of

hi ,I am writing a soft package based on R. But when I try to read a configure file showed as below. How can I read the parameter in this text file. How can I read the parameter into each variable in this file ? configinfo<-scan(file(configfile),ok=TRUE,n=-1) scan seems need every line have same column ? configinfo <- readLines(configfile,ok=TRUE,n=-1) methodnum <-

Dear R users, I have a problem with multicollinearity in mixed models and I am using lmer in package lme4. From previous mailing list, I learn of a reply "http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg38537.html" which states that if not for interpretation but just for prediction, multicollinearity does not matter much. However, I am using mixed model to interpret something,