Displaying 5 results from an estimated 5 matches for "var_model".
2010 Feb 07
1
Out-of-sample prediction with VAR
...the extra variables have no added value?
My code:
ts_Y <- ts(log_residuals[1:104]); # detrended sales data
ts_XGG <- ts(salesmodeldata$gtrends_global[1:104]);
ts_XGL <- ts(salesmodeldata$gtrends_local[1:104]);
training_matrix <- data.frame(ts_Y, ts_XGG, ts_XGL);
### Try VAR(3)
var_model <- VAR (y=training_matrix, p=3, type="both", season=NULL,
exogen=NULL, lag.max=NULL);
## Out of sample forecasting
var.lm = lm(var_model$varresult$ts_Y); # the generated LM
ts_Y <- ts(log_residuals[105:155]);
ts_XGG <- ts(salesmodeldata$gtrends_global[105:155]);
ts_XG...
2008 Aug 20
1
pdf filenames in while loop
...op here with a as the control
a=1
while(a <= 60)
{
d <- read.csv(paste(f.mat[a]), header=TRUE, sep=",")
coordinates(d) = ~dbl_1+dbl_2
variogram = autofitVariogram(dbl_5~1,d, model = c("Sph"), fix.values=c(NA,NA,NA), verbose = FALSE)
print(variogram)
print(variogram$var_model$psill[1])
print(variogram$var_model$range[2])
p <- plot(variogram, main="Semi-variogram (Spherical Model)", sub=paste("Range: ",variogram$var_model$range[2]))
print(p)
pdf(file="as.character(paste(f.mat[a])).pdf")
plot(p, main="Semi-variogram (Spherical M...
2017 Jun 29
0
Help : glm p-values for a factor predictor
It might help if you provided the code you used. It's possible that
you didn't use direction="backward" in stepAIC(). Or if you did, it
was still running, so whatever else you try will still be slow. The
statement "R provides only the pvalues for each level" is wrong: look
at the anova() function.
Bob
On 29 June 2017 at 11:13, Beno?t PELE <benoit.pele at
2009 Jun 10
2
plot two variograms on a same graph
Hi,
I would know how to plot two variograms on a same graph. I can plot one by one but I would draw both on the same one.
Is it possible? Do i need any special package?
Thanks!
Cordialement
Damien Landais
2017 Jun 29
3
Help : glm p-values for a factor predictor
Hello,
i am a newby on R and i am trying to make a backward selection on a
binomial-logit glm on a large dataset (69000 lines for 145 predictors).
After 3 days working, the stepAIC function did not terminate. I do not
know if that is normal but i would like to try computing a "homemade"
backward with a repeated glm ; at each step, the predictor with the max
pvalue would be