Dear R experts:
Here is my problem, just hard for me...
I want to generate multiple datasets, then apply a function to these
datasets and output corresponding output in single or multiple dataset
(whatever possible)...
# my example, although I need to generate a large number of variables and
datasets
seed <- round(runif(10)*1000000)
datagen <- function(x){
set.seed(x)
var <- rep(1:3, c(rep(3, 3)))
yvar <- rnorm(length(var), 50, 10)
matrix <- matrix(sample(1:10, c(10*length(var)), replace = TRUE), ncol = 10)
mydata <- data.frame(var, yvar, matrix)
}
gdt <- lapply (seed, datagen)
# resulting list (I believe is correct term) has 10 dataframes: gdt[1]
.......to gdt[10]
# my function, this will perform anova in every component data frames and
output probability coefficients...
anovp <- function(x){
ind <- 3:ncol(x)
out <- lm(gdt[x]$yvar ~ gdt[x][, ind[ind]])
pval <- out$coefficients[,4][2]
pval <- do.call(rbind,pval)
}
plist <- lapply (gdt, anovp)
Error in gdt[x] : invalid subscript type 'list'
This is not working, I tried different options. But could not figure
out...finally decided to bother experts, sorry for that...
My questions are:
(1) Is this possible to handle such situation in this way or there are other
alternatives to handle such multiple datasets created?
(2) If this is right way, how can I do it?
Thank you for attention and I will appreciate your help...
JC
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