search for: expvar

I'm trying to create a function which will allow me to subset a data set based on values of various specified variables. I also want to then apply some other function(s) (e.g., summary). This is what I've tried so far.... > test.fx <- function(dta, expvar, expval) { + newdta <- subset(dta, eval(expvar)>expval) + summary(newdta$eval(expvar)) + } > > test.fx(fyc04s, quote(totexp04), 100) Error in summary(newdta$eval(expvar)) : attempt to apply non-function > The subset works fine, but the my attempt to access the specified...

Hi all, I tried to produce some kriged surfaces with geoR (latest version). The size of the grid should be around 900 x 650 cells (what I find is not a very big grid), and the number of points is around 2500. The command krige.conv stopped after arround 5 min saying it can not allocate a vector with around 1.5 billion units. Sounds reasonable. Is there a workaround? How would I partition the

...r, the Q2cum is significantly off. Adding the Q2cum of the 1st and 2nd component comes close but that seems unconvincing and I don't understand why the 3rd component Q2cum would be so far off. Below is the code and output: pls.reg.new=plsreg2(newserumvars.sc, newtimematrix, nc=3) pls.reg.new$expvar #this provides the exact R2Y I get in SIMCAP pls.reg.new$Q2cum The Q2cum values should be close to component 1 = .2149 component 2 = .4578 *component 3 = .6627* #value of concern All of the R output values are close for the respective class except for the final Q2cum value: Q2cum.B Q2cum.FR8...

...r, the Q2cum is significantly off.? Adding the Q2cum of the 1st and 2nd component comes close but that seems unconvincing and I don't understand why the 3rd component Q2cum would be so far off.? Below is the code and output: pls.reg.new=plsreg2(newserumvars.sc, newtimematrix, nc=3) pls.reg.new$expvar? #this provides the exact R2Y I get in SIMCAP pls.reg.new$Q2cum The Q2cum values should be close to component 1 = .2149 component 2 = .4578 component 3 = .6627 #value of concern All of the R output values are close for the respective class except for the final Q2cum value: ?? Q2cum.B Q2cum.FR8 Q...

...ut that ? Then i have another question about my data. I have one response variable and about 20 explanatory variables. These variables are nested in a grouping variable of about 100 groups, which is nested in another grouping variable of 2 groups . I have tried this lme.model <- lme(respVar~expVar1, data=myData, random = respVar1+... +respVar20| groupingVariable_level2,na.action=na.omit) As i understood Snijders and Bosker, with that i have a fixed effect of expVar1 on respVar and a random effect of all the others explanatory variables. They are also nested in grouping Variable level 2. N...