Displaying 20 results from an estimated 500 matches similar to: "Course: Data exploration, regression, GLM & GAM with R introduction"
2013 Jan 14
0
Course: Introduction to zero inflated models and GLMM
We would like to announce the following statistics course:
Introduction to zero inflated models and GLMM
13 - 16 May 2013. Elche, Spain.
For details, see: http://www.highstat.com/statscourse.htm
Course flyer: http://www.highstat.com/Courses/Flyer2013_05Elche_ZIP.pdf
Kind regards,
Alain Zuur
--
Dr. Alain F. Zuur
First author of:
1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and
2013 Feb 04
0
Banff Canada: Mixed modelling course
There are 8 remaining seats on the following course:
Introduction to linear mixed effects modelling and GLMM course.
Where: Banff, Canada
When: 27-31 May, 2013
For details see the flyer at:
http://www.highstat.com/Courses/FlyerCanada2013.pdf
or: http://www.highstat.com/statscourse.htm
Kind regards,
Alain Zuur
--
Dr. Alain F. Zuur
First author of:
1. Analysing Ecological Data (2007).
2013 Jun 20
0
New book: Beginner's Guide to GLM and GLMM with R
Members of this mailing list may be interested in the following new book:
Beginner's Guide to GLM and GLMM with R.
- A frequentist and Bayesian perspective for ecologists -
Zuur AF, Hilbe JM and Ieno EN
This book is only available from:
http://www.highstat.com/BGGLM.htm
This book presents Generalized Linear Models (GLM) and Generalized
Linear Mixed Models (GLMM) based on both
2012 Jul 15
0
NaN in hurdle model please?
Simplify your model. Does your TandemRepeat have a lot of levels? Or is
your sample size very small?
Alain
Dear all,
I am
fitting a hurdle model in the following way:
HNB <-
hurdle(chro ~ as.factor(TandemRepeat)| as.factor(TandemRepeat), data =data_negbin_fin,
dist = "negbin")
But the std.
error for log(theta) = NA
Count model
coefficients (truncated negbin with log link):
2009 Nov 16
1
Paper on data exploration
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
-----
--------------------------------------------------------------------
Dr. Alain F. Zuur
First author of:
2006 Oct 08
0
3-day R course in Lisbon
Apologies for cross-posting.
We would like to announce a 3-day R course in Lisbon, Portugal.
Full details can be found at:
http://www.brodgar.com/statscourse.htm
Kind regards,
Alain Zuur
Dr. Alain F. Zuur
First author of:
Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith, GM.
Springer. 680 p.
URL: www.springer.com/0-387-45967-7
Other books: http://www.brodgar.com/books.htm
2017 Jun 20
0
New book: Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA
We are pleased to announce the following book:
Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA
Authors: Zuur, Ieno, Saveliev
Book website: www.highstat.com
Paperback or EBook can be order (exclusively) from www.highstat.com
TOC: http://highstat.com/Books/BGS/SpatialTemp/Zuuretal2017_TOCOnline.pdf
Summary: We explain how to apply linear regression models,
2013 Jan 08
0
New book: Beginner's Guide to GAM with R
Readers of this mailing list may be interested to know that the book "A
Beginner's Guide to Generalized Additive Models with R' is now available
from:
http://www.highstat.com/BGGAM.htm
Upcoming books in 2013:
A Beginner's Guide to GLM with R and JAGS.
AF Zuur, J Hilbe, EN Ieno
A Beginner's Guide to GAMM with R.
AF Zuur, AA Saveliev, EN Ieno
Kind regards,
Alain Zuur
2013 Nov 21
0
Course: Introduction to Linear mixed effects models, GLMM and MCMC with R
We would like to announce the following statistics course;
Course: Introduction to Linear mixed effects models, GLMM and MCMC with R
When: 10-14 February, 2014
Where: Pousada de juventude parque das nacoes. Rua de Moscavide, Lt 47 ?
101, 1998- 011. Lisbon, Portugal
Info: http://www.highstat.com/statscourse.htm
Flyer: http://www.highstat.com/Courses/Flyer2014_02SIM_LisbonV2.pdf
Kind regards,
2016 Apr 11
0
Intro GAM and GAMM course: Singapore
There are 4 remaining seats on the following statistics course:
Course: Introduction to GAM and GAMM with R
When: 30 May-3 June 2016
Where: Tropical Marine Science Institute, National University of
Singapore, Singapore
Course website: http://highstat.com/statscourse.htm
Course flyer: http://highstat.com/Courses/Flyers/Flyer2016_05Singapore.pdf
--
Dr. Alain F. Zuur
First author of:
1.
2016 Apr 28
0
New book: Beginner's Guide to Zero-Inflated Models with R
We are pleased to announce the following book:
Title: Beginner's Guide to Zero-Inflated Models with R
Authors: Zuur, Ieno
Book website: http://www.highstat.com/BGZIM.htm
Paperback or EBook can be order (exclusively) from:
http://www.highstat.com/bookorder.htm
TOC: http://www.highstat.com/BGS/ZIM/pdfs/TOCOnly.pdf
Keywords: 430 pages. Zero inflated count data. Zero inflated continuous
data.
2012 Jul 09
3
Predicted values for zero-inflated Poisson
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 code this.
Thanks in advance!
Laura
[[alternative HTML version deleted]]
2013 Feb 13
0
Online Beginner's Guide to R course with video/audio files
Following our successful book: 'A Beginner's Guide to R', we are please to
announce an online R course based on this book.
Video/audio files
Discussion board
Video footage of instructors
Nearly every section of ?A Beginner?s Guide to R? is covered. Each
chapter is presented as a powerpoint video file with audio comments and
you can see our computer screen with R code and results.
2013 Mar 06
0
Course: Beginner's Guide to MCMC, GLM and GAM with R
There are a few places left on the following course: Beginner's Guide
to MCMC, GLM and GAM with R
When: 10 - 13 June 2013
Where: SAMS, Oban, Scotland
Further information: http://www.highstat.com/statscourse.htm
Flyer: http://www.highstat.com/Courses/Flyer2013June_SAMS.pdf
Kind regards,
Alain Zuur
2003 Mar 23
1
export lm object to ascii from batch mode
2013 Jul 11
1
Differences between glmmPQL and lmer and AIC calculation
Dear R Community,
I?m relatively new in the field of R and I hope someone of you can
help me to solve my nerv-racking problem.
For my Master thesis I collected some behavioral data of fish using
acoustic telemetry. The aim of the study is to compare two different
groups of fish (coded as 0 and 1 which should be the dependent
variable) based on their swimming activity, habitat choice, etc.
2012 Jul 09
2
mfrow and centering plots when there's an odd number
Let me start with an example:
par(mfrow=c(2,3))
for (i in 1:5){
x = rnorm(100)
y = .5*x + rnorm(100, 0, sqrt(1-.5^2))
plot(x,y)
}
Note that there's five plots and six spaces for those plots via mfrow,
leaving one row empty. Is there a way to have the bottom two plots
centered? I think it looks weird to have them left-justified. Thanks in
advance for the help!
--
Dustin Fife
PhD
2017 Oct 31
0
Course in Lisbon: Introduction to Linear Mixed Effects Models and GLMM with R
We would like to announce the following statistics course:
Course: Introduction to Linear Mixed Effects Models and GLMM with R
Where:? Lisbon, Portugal
When:?? 19-23 February 2018
Course website: http://highstat.com/index.php/courses
Course flyer:
http://highstat.com/Courses/Flyers/2018/Flyer2018_02LisbonV2.pdf
Kind regards,
Alain Zuur
--
Dr. Alain F. Zuur
Highland Statistics Ltd.
9 St
2009 Sep 04
3
Using anova(f1, f2) to compare lmer models yields seemingly erroneous Chisq = 0, p = 1
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 summary(f2) for the
multilevel model output look perfectly reasonable), and in this case (see
below) predictor.1 explains vastly more
2009 Jul 30
1
creating subsets within lm()
Dear All,
the lm() function has the possibility to create a subset of the
possible explaining variables that you have. However, in the help
there is no example how to use this subset option. I tried the
following:
model<-lm(dependent.data$MPFD~.,data=explaining.data,subset=c(1,0,0,0,0,0,0,0,1,1,0,0))
MPFD is the dependent variable stored in the data frame
dependent.data, and all 12