Hey.
Looking at EuStockMarkets[1:1860] -- the DAX.
ar() estimates an AR(1) model with \alpha_1 ~= 1 and high \sigma^2.
But forecasting from a given X_t_0 according to an AR(1) model with \alpha_1 =
1 should be X_t_0 for all X_t, t > t_0 . ?
How do you do this forecasting in R?
predict(ar(),n.
Hi. I tried the following:
F<-function(x,y,b1,b2,b3) b1/(1+b2*(x+b3*y));
t<-data.frame(ExM=c(T$ExM,F(T$S1,T$S2,0.2,0.2,51.28205)),S1=rep(T$S1,2),S2=rep(T$S2,2),gr=c(rep(1,length(T$ExM)),rep(2,length(T$ExM;
library(lattice);
wireframe(ExM ~ S1 * S2, data = t, groups=gr);
where
Hi. Thanks for your help with my previous question (comparing two lm() models
with a maximum likelihood ratio test)
I had a look at lrtest from the package lmtest as it has been suggested to me,
but I am not 100% sure if that is the right thing to do ...
lrtest uses the same log likeliho
Hi.
I would like to use a likelihood-ratio test to compare a linear model (lm()) to
another linear model containing the first one to see if the extra factors are
needed - but I was unable to find any help on how to do that.
Could you help me and tell me what to do? Or tell me where to find
Hey!
Could you please take a quick look at what I have done? Somehow I get wrong
results using the anova(lm()) combination compared to doing a two way ANOVA by
hand.
Running:
Data<-read.table("Data.txt");
g<-lm(ExM~S1*S2,Data);
anova(g);
Gives:
Analysis of Variance Table
Res
Hi.
I have the following two ecdf plots in one graph:
plot(
ecdf(),
do.points=FALSE,
verticals=TRUE,
main=paste("Ecdf of distances ",DIM,sep=""),
col="red"
);
lines(
ecdf(),
do.points=FALSE,
verticals=TRUE
);
How do I change the color of the resulting graph?
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