Hi,
   
  Someone help-me on this task some weeks ago, and it is working find to me. I use something like:
  -----
  findmodels <- function(modeltype = "lm", dataset, pattern) {
 ls <- ls(".GlobalEnv", pattern=pattern)
 mods <- ls[sapply(ls, function(x) inherits(get(x), modeltype))]
 if (!missing(dataset)) {
 data.name <- function(x) as.character(x$call[["data"]])
 mods <- mods[sapply(mods, function(x) data.name == dataset)]
 }
 models <- lapply(mods, get)
 class(models) <- c("ensemble", class(models))
 models
 }
   
  mod_1<-glm(....)
  mod_2<-glm(....)
   
  models<-NULL
models<- findmodels(pattern="mod_")
  -------------

  So you can use a "for (i in 1:length(models))" to extract the statistics tha you want for each model and save it in a file (I´m saving it easily in Access using RODBC).
   
  I hope this help,
   
  Miltinho
  Brazil
  
Indermaur Lukas <Lukas.Indermaur@eawag.ch> escreveu:
  Hello

I want to batch job the calculation of many GLM-models, extract some values and store them in a file. Almost everything in the script below works (read file, extract values and write them to file) except I fail in indexing the GLM with the modelstructure it should run. Running GLM's conventionally is no problem.



Conventionally a GLM is calculated as:

--------------------------------------

glm(ZlogHRS ~ ZRi+ZE+ZPROX_MN+ZED+ZAlwd+ZT2+ZW+ZN+Sex+y, family = gaussian, data=t.data) 

(just a note: dependent variable is ZlogHRS, while the others are indepent variables)



Desired way: sequentially run GLM

---------------------------------

I want R to take the model structure to take from a vector called "modelstructure" and paste it into the GLM like:

glm(modelstructure[i], family = gaussian, data=t.data).

It would considerably ease my workload if there is a solution to the indexing problem within a GLM. I appreciate any hint.

Best regards

Lukas

p.s.

my R skills are rather poor



----------------------------------------START R-CODE-----------------------------------

# Read file

t.url <- "C://HR_calculations/2005_2006/HR_SIZE/Kandidatenmodelle_Berechnung/inputfiles/"

t.tuti <- read.table(paste(t.url, "All_animals.txt", sep=""),header=T)



collect.results <- function(x) {

#resets vectors which will be filled

i <- 0

AICA <- NA;



#put models names hierarchically in vector

modelnames <- c("1=global", "2=biotic1", "3=biotic2", "4=abiotic") #keep track of changes in model names and number

for (i in 1:length(modelnames)) 

#model structure of the four models given for all models to run

#global

modelstructure <- c(

"ZlogHRS ~ ZRi+ZE+ZPROX_MN+ZED+ZAlwd+ZT2+ZW+ZN+Sex+y",

#biotic1

"ZlogHRS ~ ZRi",

#biotic2

"ZlogHRS ~ ZPROX_MN",

#abiotic

"ZlogHRS ~ ZE")



ts.model <- glm(modelstructure[i], family = gaussian, data=t.data) 



# Extracts some mode results

n[i] <- length(resid(ts.model))

AICA[i] <- AIC(ts.model)

}

#Writes results to data file

x = data.frame(

modelnames, n, AICA)

write.table(x, paste(t.url, file="Results.txt"), sep="\t", quote=F) 

----------------------------------------END R-CODE-----------------------------------








°°° 
Lukas Indermaur, PhD student 
eawag / Swiss Federal Institute of Aquatic Science and Technology 
ECO - Department of Aquatic Ecology
Überlandstrasse 133
CH-8600 Dübendorf
Switzerland

Phone: +41 (0) 71 220 38 25
Fax : +41 (0) 44 823 53 15 
Email: lukas.indermaur@eawag.ch
www.lukasindermaur.ch

______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


 __________________________________________________


	[[alternative HTML version deleted]]

