" differ from the results of "anova(m1, type
>>> = "marginal")" and "summary(m1)."
>>>
>>> Thanks for your help,
>>>
>>Haven't spent a lot of time thinking this through, but I'm guessing
>
ce of the variables - something like in this graph (
> http://dl.dropbox.com/u/52403158/F_value_plot.png). My number of samples
> is
> always the same (n=5478), but the number of terms in each areas model can
> be different, and of course the degrees of freedom in the smooth terms are
&g
n the bootstrapping code that
would produce such a graphical output would be appreciated, especially
since I am new to the bootstrapping coding.
I hope that is clear and thanks in advance for any help that anyone can
offer.
--
Basil Iannone
University of Illinois at Chicago
Department of Biologic
w()
y1<-c(min(Y), max(Y))
x1<-c(min(X), max(X))
plot(effect('X', m1), xlim = x1, ylim = y1)
points(Y~X, pch = 16, col = "black")
Thanks a bunch for any suggestions that anyone can offer.
--
Basil Iannone
University of Illinois at Chicago
Department of Biological Scienc
Q1 Med Q3 Max
-2.68192339 -0.67510193 -0.05998944 0.56286828 2.55012832
Residual standard error: 45.15951
Degrees of freedom: 96 total; 93 residual
--
Basil Iannone
University of Illinois at Chicago
Department of Biological Sciences (MC 066)
845 W. Taylor St.
Chicago,
link to the file describing
"anova" (just an example).
I am using a PC with Windows XP. I was wondering if anyone else out there
has had similar problems, and if so, how you resolved this issue. I
searched for a while online, but could not find a resolution.
Thanks for the help,
--
Bas
using R on my computer for a long time without this issue.
2) I believe the version of R that I am using is the current version.
I will try out the actions that you suggested. Thanks for the help.
On Wed, Sep 19, 2012 at 1:58 AM, Ivailo wrote:
> On Wed, Sep 19, 2012 at 2:39 AM, Basil Iannone wr
Dear R users,
I am trying to conduct a simprof analysis to determine if groups of objects
form statistically significant clusters.
The variables that I am using are a mixture of categorical, ordered, and
numerical. I am therefore using Gower's distance for this analysis. Below
is the code with my
null hypothesis
> testing for community data: similarity profiles and biota-environment
> linkage. J Exp Mar Biol Ecol 366, 56-69
>
>
> Best,
>
> ---
> Md. Abdul Halim
> Assistant Professor
> Department of Forestry and Environmental Science
> Shahjalal
gt; CLARKE KR, SOMERFIELD PJ, GORLEY RN (2008) Exploratory null hypothesis
>> > testing for community data: similarity profiles and biota-environment
>> > linkage. J Exp Mar Biol Ecol 366, 56-69
>> >
>> >
>> > Best,
>> >
>> > ---
>
Valarie,
I too ran across this problem. vegmite operates on data with a single digit
such as Braun-Blanquet cover estimates. Thus vegemite command will not work
on data such as environmental data or biomass data unless you convert it to
a single digit, causing you to loose a lot of information. So
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