On Feb 18, 2014, at 9:47 AM, Amanuel Tekleab wrote:
> Hi all,
>
> I am a facing a convergence problem when I test for variability of a slope
> among groups in lme.
> a) How do I know how many iterations the program is running?
> b) How do I increase the # of iterations
> c) Do I include the comm
Hi all,
I am a facing a convergence problem when I test for variability of a slope
among groups in lme.
a) How do I know how many iterations the program is running?
b) How do I increase the # of iterations
c) Do I include the command to increase iterations in my equation?
Thanks for your help!
Am
On Sat, 28 Nov 2009, Sarah Valencia wrote:
Hello,
I have a data frame with 1425 observations, 539 of which are zeros. I
am trying to fit the following ZINB:
f3<-formula(Nbr_Abs~ Zone * Year + Source)
ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData,
offset=log(trans.area), trace=
Hello,
I have a data frame with 1425 observations, 539 of which are zeros. I
am trying to fit the following ZINB:
f3<-formula(Nbr_Abs~ Zone * Year + Source)
ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData,
offset=log(trans.area), trace=TRUE)
Zone is a factor with 4 levels, Year a
623 12.49623
>
> Xr.19 Xr.110
> Xr.111 Xr.112 Xr.113
> Xr.114 Xr.115 Xr.116
>
> StdDev:
> 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623
>
> Xr.117 Xr.118
> Xr.119 Xr.120 Xr.121
> Xr.122 Xr.123 Xr.124
>
: ~Xr.1 - 1 | g.1
>
> Structure: pdIdnot
>
>Xr.11Xr.12
> Xr.13Xr.14Xr.15
> Xr.16Xr.17Xr.18
>
> StdDev:
> 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623 12.49623
>
>Xr.19 Xr.110
> Xr.111 Xr.112 Xr.113
&
-
> From: s.w...@bath.ac.uk
> To: r-help@r-project.org
> Date: Fri, 23 Jan 2009 11:32:21 +
> Subject: Re: [R] convergence problem gamm / lme
>
> Geert,
>
> Can you get a simpler model with, say, a quadratic dependence on lon, lat to
> converge, using glmmPQL? The a
Geert,
Can you get a simpler model with, say, a quadratic dependence on lon, lat to
converge, using glmmPQL? The answer might give a clue about whether the issue
is related to using a smoother, or is something more basic.
How confident are you that the Poisson assumption is reasonable?
Can th
Hope one of you could help with the following question/problem:
We would like to explain the spatial
distribution of juvenile fish. We have 2135 records, from 75 vessels
(code_tripnr) and 7 to 39 observations for each vessel, hence the random effect
for code_tripnr. The offset (offsetter) ac
I'm grateful for your kind help.
I've clearly got the idea and am relieved.
As for question 1, the value of mgcv.conv$rms is small (less than
1.E-5 while GCV being around 1).
For question 2, as I don't have other reasons to doubt the linearity,
I guess the result is OK.
Sincerely,
Ariyo
2007/1
Actually the answers to you questions may well be linked
On Thursday 04 October 2007 22:11, Ariyo Kanno wrote:
> Dear all,
>
> I'm trying to fit a pure additive model of the following formula :
> fit <- gam(y~x1+te(x2, x3, bs="cr"))
> ,with the smoothing parameter estimation method "magic"(de
Dear all,
I'm trying to fit a pure additive model of the following formula :
fit <- gam(y~x1+te(x2, x3, bs="cr"))
,with the smoothing parameter estimation method "magic"(default).
Regarding this, I have two questions :
Question 1 :
In some cases the value of "mgcv.conv$fully.converged" becomes
"
Hello, folks
when I ran my boolean logit model in R, I got an error message as
> answer <- boolean (bp, link = "logit", method = "BFGS", data=pr2)
27061 observations dropped due to missing data.
Warning message:
fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y
= Y, weights =
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