Displaying 2 results from an estimated 2 matches for "var_num".
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2009 Jan 24
2
how to prevent duplications of data within a loop
...<- rnorm(50)
var1 <- rnorm(50)
var2 <- rnorm(50)
var3 <- rnorm(50)
myData <- data.frame(response,var1,var2,var3)
var.names <- names(myData)[2:4]
numVars <- length(var.names)
betas <- rep(-1,numVars)
names(betas) <- var.names
#run regression on var1 through var3.
for (Var_num in 1:numVars)
{
col.name <- var.names[Var_num]
mylm <- lm(response ~ get(col.name),data=myData,model=FALSE)
betas[Var_num] <- coef(mylm)[2]
}
2009 Jan 22
0
detecting the source of memory consumption (example provided)
...place=TRUE)
id <- rep(1:25,each=2)
var1 <- rnorm(50);
var2 <- rnorm(50);
var3 <- rnorm(50);
myData <- data.frame(response,x1,age,id,var1,var2,var3)
numVars <- ncol(myData)-4;
pvalues <- rep(-1,numVars);
names(pvalues) <- colnames(myData)[5:ncol(myData)];
library(yags)
for (Var_num in 1:numVars)
{
fit.yags <- yags(myData$response ~
myData$age+myData$x1*myData[,(Var_num+4)], id=myData$id,
family=gaussian,corstr="exchangeable",alphainit=0.05)
z.gee <- fit.yags at coefficients[5]/sqrt(fit.yags at robust.parmvar[5,5]);
pval <- 2 * pnorm(abs(z.gee), low...