Displaying 4 results from an estimated 4 matches for "bcoef".
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2007 Oct 03
2
Shading area under density curves
...ng regions under curves to display
95% confidence intervals. I generated bootstrap results for the slope
and intercept of a simple linear regression model using the following
code (borrowed from JJ Faraway 2005):
> attach(allposs.nine.d)
> x<-model.matrix(~log(d.dist,10))[,-1]
> bcoef<-matrix(0,1000,2)
> for(i in 1:1000){
+ newy<-predict(all.d.nine.lm)+residuals(all.d.nine.lm)[sample(1002,rep=TRUE)]
+ brg<-lm(newy~x)
+ bcoef[i,]<-brg$coef
+ }
Where "allposs.nine.d" is a data file composed of two columns: (1)
geographical distances between sample point...
2012 Mar 18
1
Help with dlply, loop and column names
...loop I'm coming into trouble and I'm at the
moment really confused how to solve this problem:
I have the following function:
elecregtipos <- function(y){
z<-dlply(asturias.gen2011, .(tipo), function(x) lm(x[,y]~x$edad.media))
# rsq<-function(x) summary(x)$r.squared
# bcoefs<-ldply(z, function(x) c(coef(x), rsquare=rsq(x)))
# return (bcoefs)
return(z)
}
And I try to call it with:
for (y in c("upyd", "psoe", "pp", "fac", "iu")) {
eval(parse(text=paste(y,'.lm.tipos', '<- elecregtipos(',...
2007 Jun 20
2
Extracting t-tests on coefficients in lm
I am writing a resampling program for multiple regression using lm(). I
resample the data 10,000 times, each time extracting the regression
coefficients. At present I extract the individual regression
coefficients using
brg = lm(Newdv~Teach + Exam + Knowledge + Grade + Enroll)
bcoef[i,] = brg$coef
This works fine.
But now I want to extract the t tests on these coefficients. I cannot
find how these coefficients are stored, if at all. When I try
attributes(brg)
I do not find the t values as the attributes of the object. Typing
summary(brg) will PRINT the coefficients, th...
2012 Nov 21
0
Question about VAR (Vector Autoregression) in differences.
...Rpath<-function(object, n.ahead, mult = 1) {
K <- object$K
p <- object$p
obs <- object$obs
type <- object$type
data.all <- object$datamat
ynames <- colnames(object$y)
n.ahead <- as.integer(n.ahead)
Z <- object$datamat[, -c(1:K)]
B <- Bcoef(object)
if (type == "const") {
Zdet <- matrix(rep(1, n.ahead), nrow = n.ahead, ncol = 1)
colnames(Zdet) <- "const"
}
else if (type == "trend") {
trdstart <- nrow(Z) + 1 + p
Zdet <- matrix(seq(trdstart, length = n....