What statistical measure(s) tend to be answering ALL(?) question of practical
interest?
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My suggestion:
If compare model 1 and model 2 with model 0 respectively, the (penalized)
likelihood ratio test is valid.
IF you compare model 2 with model 3, the (penalized) likelihood ratio test
is invalid. You may want to use AIC/SBC to make a subjective decision.
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I didn't see any error when I ran your code in my computer:
> numbers <- c(1134,956,328,529,435,599,27,99)
> dim(numbers) <- c(2,2,2)
> numbers
, , 1
[,1] [,2]
[1,] 1134 328
[2,] 956 529
, , 2
[,1] [,2]
[1,] 435 27
[2,] 599 99
> dimnames(numbers)[[3]] <-list("Mussels", "
The likelihood ratio test is more reliable when one model is nested in the
other. This true for your case.
AIC/SBC are usually used when two models are in a hiearchical structure.
Please also note that any decision made
made based on AIC/SBC scores are very subjective since no sampling
distributio
The following code shows that the unlisted data frame assigns an index to
each member. When one sorts the data frame based on ULST, he in fact uses
the (implicit) indices of ULST but not the actual values! Therefore, your
guess is correct.
> test.vec=data.frame(c("A","F","C"))
> ULST=unlist(test.
Sorry for possible misunderstanding:
I want to define a matrix (B) based on an existing matrix (A) in a single
step and keep A unchanged:
> #Existing matrix
> A=matrix(1:16,ncol=4)
> A
[,1] [,2] [,3] [,4]
[1,]159 13
[2,]26 10 14
[3,]37 11 15
[4,]4
Try this:
> LinePlot(1,1)
> LinePlot=function(a,b){
+ # a = slope
+ # b = y intercept
+ x=seq(-10,10,0.4)
+ y=a*x+b
+ plot(x,y, type="l")
+ title(paste("a=",a,"b=",b))
+ }
>
> #test
> LinePlot(a=-2,b=9)
HTH
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the deteminant is a nonpositive value. log(det(...)) produce NaNs...
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Thanks to De-Jian and Peter. Peter's way is neat and cool!
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Thanks Josh and Karl. function dnrm() works well for my purpose.
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Thanks for all suggestions from Roman (?= 500600[via R]), Barry and Jim.
It seems that ls()[-objectname] didn't work even on numeric matrices and
user made functions. I will work with Jim's advice on using grep() and gc()
to see whether it works.
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How to remove all R objects in the RAM except for a few specified ones?
rm(list=ls()) removes all R objects in the R work space.
Another question is that whether removing all R objects actually releases
the RAM? Thanks.
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