Hi all,
I have a doubt with multiple regression. I have this model:
y ~ x + w + z
but the response y to z is humped. I check this by plot and run:
lm(y ~ z + I(z^2) # better r-square that lm(y ~ z)
I'd like use this response with quadratic term in multiple regression. I
think that if I use
On Mon, 2010-05-31 at 13:44 +1000, Zhongkui Luo wrote:
Dear all,
# I have the following sub-datasets of soil carbon change at four sites.
There are four treatments at each site.
DltC - c(-19.237, -14.857, -14.818, -14.815, -11.014, 3.349, 4.332, 3.956,
-7.638, 9.469, 14.189, 13.037,
Dear all,
# I have the following sub-datasets of soil carbon change at four sites.
There are four treatments at each site.
DltC - c(-19.237, -14.857, -14.818, -14.815, -11.014, 3.349, 4.332, 3.956,
-7.638, 9.469, 14.189, 13.037, -9.809, 5.459, 8.748, 11.511)
# Soil C fractions at the start of
On Tue, Feb 16, 2010 at 11:15 PM, David Hewitt dhewit...@gmail.com wrote:
Date: Sun, 14 Feb 2010 17:15:02 -0700
From: Kingsford Jones kingsfordjo...@gmail.com
To: gustaf.gran...@ebc.uu.se
Cc: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] multiple regression
Message-ID
Date: Sun, 14 Feb 2010 17:15:02 -0700
From: Kingsford Jones kingsfordjo...@gmail.com
To: gustaf.gran...@ebc.uu.se
Cc: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] multiple regression
Message-ID:
2ad0cc111002141615w178722c7u1e47315a7b8aa...@mail.gmail.com
Content-Type: text
Sent: Saturday, February 06, 2010 5:17 PM
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] multiple regression
Hi everyone,
I'm trying to fit a multiple regression model and have run into some
questions regarding the appropriate procedure to use. I am trying to
compare
fish
lemoine.nat...@gmail.com
Sent: Saturday, February 06, 2010 5:17 PM
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] multiple regression
Hi everyone,
I'm trying to fit a multiple regression model and have run into some
questions regarding the appropriate procedure to use. I am trying
Hi Nathan,
I fould this paper by Zuur and co-workers,
2009http://www3.interscience.wiley.com/journal/122683826/abstract?CRETRY=1SRETRY=0,
very insightful. While step-wise modeling is something The R book presents,
it may or may not be the best way to do it. Read the paper and judge for
yourself
Message: 1
Date: Mon, 8 Feb 2010 11:02:37 +0100
From: ONKELINX, Thierrythierry.onkel...@inbo.be
To: Peter Solymossoly...@ualberta.ca, Nathan Lemoine
lemoine.nat...@gmail.com
Cc: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] multiple regression
Message-ID
Dear Alain,
Thank you for your comments.
Interesting thought. Maybe correct. But there are a few
things to think
about:
1. You have to assume that sampling was such that all species
out there have ended up in the data. Formulated
differently...you need to know the N_i (maximum number of
Onderwerp: Re: [R-sig-eco] multiple regression
On Mon, 2010-02-08 at 11:02 +0100, ONKELINX, Thierry wrote:
Peter,
I would think that the species richness is binomial distributed. Since
there is a maximum number of species that can be present. Therefore I
would model it like
glm(cbind
answer can be extracted from a given body of data.
~ John Tukey
-Oorspronkelijk bericht-
Van: Gavin Simpson [mailto:gavin.simp...@ucl.ac.uk]
Verzonden: maandag 8 februari 2010 11:14
Aan: ONKELINX, Thierry
CC: Peter Solymos; Nathan Lemoine
Onderwerp: Re: [R-sig-eco] multiple regression
/stats/faq/faq12.asp
Cheers,
Aitor
--
From: Nathan Lemoine lemoine.nat...@gmail.com
Sent: Saturday, February 06, 2010 5:17 PM
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] multiple regression
Hi everyone,
I'm trying to fit a multiple
Perth, Australia 6150
j.fonta...@murdoch.edu.au
From: r-sig-ecology-boun...@r-project.org on behalf of Aitor Gastón
Sent: Tue 2/9/2010 2:19 AM
To: Nathan Lemoine; r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] multiple regression
Hi Nathan,
Many authors
Hi Nathan,
I only quickly read your email, but I believe you were asking about step-wise
regression. I would strongly suggest that instead you consider using multimodel
inference (Burnham Anderson). If you want I can suggest for you a couple of
papers to read in order to learn more about
Nathan,
Species richness is categorical, so if your richness values are
usually low (say 20), you should consider the use of Poisson GLM, or
log-transform your response (and log is the canonical link function
for Poisson GLM). This usually improves the model fit. And this might
apply to
I meant Species richness is discrete, not categorical.
Peter
On Sat, Feb 6, 2010 at 12:52 PM, Peter Solymos soly...@ualberta.ca wrote:
Nathan,
Species richness is categorical, so if your richness values are
usually low (say 20), you should consider the use of Poisson GLM, or
log-transform
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