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 to
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
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=feedburnerutm_medium=feedutm_campaign=Feed%3A+wordpress%2Fmethodsblog+(methods.blog)
All data and R code is available.
Alain
-
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)
I guess that
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 linear
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?
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
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
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
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, Aug 7, 2009
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
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 very
:
lm(blah blah, data=explaining.data[, pick your columns])
Alain Zuur
-
Dr. Alain F. Zuur
First author of:
1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
2. Mixed effects models
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
-
Dr. Alain F. Zuur
First author of:
1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith
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 not just
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 be the
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 graph
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 data.
Alain Zuur
--
View this message in context:
http://www.nabble.com/Zinb-for-Non-interger-data
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 I
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_raw_data_NAomitted is my data frame.It has columns
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