Displaying 5 results from an estimated 5 matches for "mabille".
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camille
2012 May 29
1
strucchange Fstats() example
...tected by the breakpoints() function. Does anyone know how this is possible? I'm totally new to strucchange so it might well be something obvious I'm missing here!
OTHER SIDE QUESTION: can strucchange be used if the y variable is binary???
Thanks heaps if anyone can help
Geraldine
From: Mabille, Geraldine
Sent: 29. mai 2012 11:30
To: 'r-help@r-project.org'
Subject: GAM interactions, by example
Dear all,
I'm using the mgcv library by Simon Wood to fit gam models with interactions and I have been reading (and running) the "factor 'by' variable example" given...
2012 Apr 02
1
gamm: tensor product and interaction
Hi list,
I'm working with gamm models of this sort, using Simon Wood's mgcv library:
gm<- gamm(Z~te(x,y),data=DATA,random=list(Group=~1))
gm1<-gamm(Z~te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1))
with a dataset of about 70000 rows and 110 levels for Group
in order to test whether tensor product smooths vary across factor levels. I was wondering if comparing those two
2012 May 29
1
GAM interactions, by example
Dear all,
I'm using the mgcv library by Simon Wood to fit gam models with interactions and I have been reading (and running) the "factor 'by' variable example" given on the gam.models help page (see below, output from the two first models b, and b1).
The example explains that both b and b1 fits are similar: "note that the preceding fit (here b) is the same as
2012 Apr 25
1
random effects in library mgcv
Hi,
I am working with gam models in the mgcv library. My response variable (Y) is binary (0/1), and my dataset contains repeated measures over 110 individuals (same number of 0/1 within a given individual: e.g. 345-zero and 345-one for individual A, 226-zero and 226-one for individual B, etc.). The variable Factor is separating the individuals in three groups according to mass (group 0,1,2),
2012 Mar 29
0
multiple plots in vis.gam()
Hi,
I'm working with gamm models of this sort:
gm<- gamm(Z~te(x,y),data=DATA,random=list(Group=~1))
gm1<-gamm(Z~te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1))
with a dataset of about 70000 rows and 110 levels for Group
if I use plot(gm1$gam), I obtain 3 different surface plots, one for each level of my factor but I would like to create more complex contour plots for those 3