Lee, Laura wrote
>
> Hi all-
>
> I fit a zero-inflated Poisson model to model bycatch rates using an offset
> term for effort. I need to apply the fitted model to a datasets of varying
> levels of effort to predict the associated levels of bycatch. I am seeking
> assistance as to the correct way
Haiyang AI wrote:
>
> Dear all,
>
> I'm a beginner of R and I need to carry out some three-way mixed ANOVAs.
> Following examples at http://personality-project.org/r/r.anova.html, I
> managed to get the ANOVA part, but I don't know how can I check data
> normality and homogeneity of variance in
R users doing data analysis may be interested in the following paper:
http://methodsblog.wordpress.com/2009/11/13/first-paper-now-online/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+wordpress%2Fmethodsblog+(methods.blog)
All data and R code is available.
Alain
-
---
R_help Help wrote:
>
> Hi - I read through dse package manual a bit. I'm not quite certain
> how I can use it to estimate a time varying coefficient regression
> model? I might pick up an inappropriate package. Any suggestion would
> be greatly appreciated. Thank you.
>
>
> Just rewrite the l
atorso wrote:
>
> Hello,
>
> I'm having an error when trying to fit the next GLM:
>
>>>model<-glm(response ~ CLONE_M + CLONE_F + HATCHING
> +(CLONE_M*CLONE_F) + (CLONE_M*HATCHING) + (CLONE_F*HATCHING) +
> (CLONE_M*CLONE_F*HATCHING), family=quasipoisson)
>>> anova(model, test="Chi")
>
>
>
>
RS27 wrote:
>
> Hi,
> I am trying to add multiple variance structures such as the first example
> below:
>
> vf1 <- varComb(varIdent(form = ~1|Sex), varPower())
>
> However my code below will not work can anybody please advise me?
>
> VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(f
rapton wrote:
>
> Hello,
>
> I am using R to analyze a large multilevel data set, using
> lmer() to model my data, and using anova() to compare the fit of various
> models. When I run two models, the output of each model is generated
> correctly as far as I can tell (e.g. summary(f1) and summ
rapton wrote:
>
> Hello,
>
> I am using R to analyze a large multilevel data set, using
> lmer() to model my data, and using anova() to compare the fit of various
> models. When I run two models, the output of each model is generated
> correctly as far as I can tell (e.g. summary(f1) and summ
Ben Bolker wrote:
>
> My two cents: this is a hard problem to do, period (not just in R).
> I would second the recommendation of the Dormann et al paper listed
> below; also see Zuur, Alain F., Elena N. Ieno, Neil J. Walker, Anatoly A.
> Saveliev, and Graham M. Smith. Mixed Effects Models and E
annie Zhang wrote:
>
> Hi, Milton,
>
> Thank you for the reply. I tried, but it seems the problem is the column
> name of the test data is not the same as the column name of the training
> data. I didn't give the column name, the system seemed do. How to chang
> here?
>
> Annie
>
> On Fri, Au
Mark Na wrote:
>
> Dear R-helpers,
> I would like to compare the fit of two models, one of which I fit using
> lm()
> and the other using glm(family=poisson). The latter doesn't provide
> r-squared, so I wonder how to go about comparing these
> models (they have the same formula).
>
> Thanks v
Thiemo Fetzer wrote:
>
> Dear Group,
>
> I am an economics student starting with PhD work in London. As preparation
> I
> would like to get to know R a little bit better. For Stata there are tons
> of
> books, however, can you recommend a book for R?
>
> I have some substantiated econometrics
Hadassa Brunschwig-2 wrote:
>
> Hi all
>
> I have been looking (in the help archives) for a function
> which does a moving average. Nothing new, I know.
> But I am looking for a function which is very flexible:
> The user should be able to input a vector of breaks
> which define the bins (and n
the link to the R book).
It was quite a challenge to do this...not because of the R code (we used
Murrel, 2006)...but because of figuring out the optimal the size of the jpg.
R didn't like to use the original 5Mb jpg file. So..I had to reduce it size.
Alain Zuur
-
-
_
>
>
The subset option works on the rows of the data set. Not on the covariates.
You would have to do something like:
lm(blah blah, data=explaining.data[, pick your columns])
Alain Zuur
-
Data Analytics Corp. wrote:
>
> Hi,
>
> I wrote a simple master function, run(), that has inside six qplot
> functions. The goal is to type run() and have all six graphs appear as
> separate windows so that I can copy them into PowerPoint for a client.
> When I type run(), only the last gr
cindy Guo wrote:
>
> Hi, All,
>
> I have a dataset with binary response ( 0 and 1) and some numerical
> covariates. I know I can use logistic regression to fit the data. But I
> want
> to consider more locally. So I am wondering how can I fit the data with
> 'loess' function in R? And what will
Read the warning message! It has converted your variables into factors.
Figure out why...and you will have solved the problem.
Alain Zuur
moumita wrote:
>
> *
> *
>
> Hi ,
>
> Can anyone help me please with this problem?*
> *
>
> *CASE-I*
>
> all_ra
Rbeginner wrote:
>
> Hi everyone!
> I'm new to R, and I've sent this message as a non-member, but since it's
> pretty urgent, I'm sending it again now I'm on the mailing list (Thanks
> Daniel for your suggestion nevertheless).
>
> I have calculated a regression in the form of M ~ D + O + S, and
n on the second part of the
data..and I guess the easiest is to do this in MCMC. Perhaps the Gamma
distribution can be used? You would have to adjust all likelihood equations
as Gamma doesn't allow for zeros. But perhaps another continuous
distribution is more appropriate...depends on your dat
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