similar to: Course: Data exploration, regression, GLM & GAM with R introduction

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