Howdy,
TWINSPAN is not in CRAN. It seems that you found it in github.
TWINSPAN is an old method, and it seems that people are forgetting how it
works. Here some narrative:
First, you have defined cut levels to transform your abundance data into binary
indicator “pseudospecies”. You give these
e is no need to think it as an ordination.
Cheers, Jari Oksanen
On 7 Nov 2019, at 22:02, Couch, Claire Elizabeth
mailto:cou...@oregonstate.edu>> wrote:
I am analyzing some microbiome data by using unconstrained ordination (PCA
or NMDS) followed by environmental vector fitting with the envf
?printCoefmat which explains the usage of
stars.
Cheers, Jari Oksanen
> On 25 Sep 2019, at 20:51, melissa schindler
> wrote:
>
> Hello all,
>
> I have run a redundancy analysis on Hellinger transformed species abundance
> data and environmental variables.
>
> Once I
Yes, it is possible, and always has been when I have checked (which is not a
proof). You can check this by seeing that it has no negative eigenvalues in
principal coordinates analysis (apart from occasional negative almost-zero).
Legendre & Legendre book discuss this.
Cheers, Jari Oks
/vegan/.
cheers, Jari Oksanen
On 11 Jan 2019, at 20:09, Charlotte Reemts
mailto:cree...@tnc.org>> wrote:
I am using EcoTest.sample (rareNMtests package) to compare rarefaction curves
for 19 vegetation plots on two soil types (alluvial and canyon). The code below
produces the following warning
Marc, the source code of those slides is in
https://github.com/jarioksa/ordination101/. Look at the source code to see how
the slide was generated.
cheers, Jari Oksanen
On 7 Dec 2018, at 09:34, Marc Taylor
mailto:marchtay...@gmail.com>> wrote:
Thanks Franz!
cheers, Marc
On Fri, Dec 7
rowhouse, data =
metadata_fungi_out, permutations = , by = "margin")
Df SumOfSqs R2 F Pr(>F)
Stage:Growhouse 3 1.0812 0.23075 1.9998 0.006 **
Residual20 3.6045 0.76925
Total 23 4.6857 1.0
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01
.48769 2.7060 0.10408 0.0247 *
> Growhouse10.3765 0.37647 2.0889 0.08034 0.0542 .
> Stage:Growhouse 10.2171 0.21708 1.2045 0.04633 0.2507
> Residuals 203.6045 0.18023 0.76925
> Total 234.6857 1.0
> ---
> Signi
these tests were
implemented, but you may do that in your leisure if you think this is what you
want to have.
Cheers, Jari Oksanen
> On 16 Oct 2018, at 14:53 pm, Ellen Pape wrote:
>
> Hi,
>
> I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
> specifyi
n alone.
> ~A*B unfolds to ~A+B+A:B
Well, it was correct: the only **marginal** effect in ~A+B+A:B is A:B (A
and B are not marginal), and by = "margin" will only analyse marginal
effects.
Cheers, Jari Oksanen
>
> On Tue, 16 Oct 2018 at 11:51, Ellen Pape wrote:
>
>>
them: it’s all up to your
responsibility.
cheers, Jari Oksanen
> On 14 Oct 2018, at 19:07 pm, Irene Adamo wrote:
>
> Dear all,
> I would like to create a distance matrix based on the similarity
> Chao-Jaccard index based on raw abundances in R but so far I have not been
> able
umentation (?metaMDS).
Have you worked like suggested in that document? What failed when you followed
the instructions?
Cheers, Jari Oksanen
From: R-sig-ecology on behalf of Chitra
Baniya
Sent: 22 November 2017 05:52
To: r-sig-ecology@r-project.org
actor. Contributions are welcome at http://github.com/vegandevs/vegan.
cheers, Jari Oksanen
From: R-sig-ecology on behalf of Andrew
Halford
Sent: 08 February 2017 10:14
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] Factors in partial RDA part 2
Hi Li
one of the dummy
variables, R will do it for you and tell that some of your original variables
were aliased. This will not influence the results, though.
In conclusion: everything goes, but it is best to use the R way and define your
factor as a single factor.
Cheers, Jari Oksanen
> On 7
Ansley, I think you may have an old version of clustsig: the current one should
not give an error of missing undef.zero. Please check if you need to update.
cheers, j.o.
> On 7 Oct 2016, at 19:21 pm, Sarah Goslee wrote:
>
> I can't duplicate your error. Assuming the attached document describes
Think about it.
Cheers, Jari Oksanen
From: R-sig-ecology on behalf of Ansley
Silva
Sent: 04 August 2016 23:30
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] raremax value >2, cannot run rarefy
Hello,
R version 3.2.2, using the vegan package.
I a
Ewan,
You already got some good hints from Peter Michin (outside this list), but here
some comments.
> On 2 May 2016, at 20:22 pm, Ewan Isherwood wrote:
>
> Hi r-sig-ecology!
>
> This is mostly a message for Jari Oksanen or another Vegan developer that
> may be working
haelis-Menten equation”. Michaelis-Menten is
available in fitspecaccum() in vegan.
Cheers, Jari Oksanen
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dination instead of raw data: no
> ecological relevant information is lost, only the 'noise' is reduced.
>
> Best wishes
>
> Zoltan
>
> 2016.01.11. 11:11 keltezéssel, Jari Oksanen írta:
>> Contrary to common misbelief, NMDS ordination space is **metric**.
> On 11 Jan 2016, at 14:13 pm, Bob O'Hara wrote:
>
>
> Whilst I'm filling bandwidth, I'm not sure Jari's suggestion that you need
> the interaction term is correct. If a model is linear in axis1 and axis2,
> then any rotation is also linear, i.e. the transformation is c_1 axis1 + c_2
> axis2
parallel to the axes) is good and you have an indicator variable for that, you
can use MDSrotate() function in vegan to rotate your solution to that direction
and then take that rotated axis as your explanatory variable.
HTH, Jari Oksanen
> On 11 Jan 2016, at 10:38 am, Martin Weiser wr
the names may
be used loosely. There is also Horn index that is not implemented in
vegan::vegdist. For these indices, vegan follows Krebs’s “Ecological
Methodology”.
cheers, Jari Oksanen
> On 27 Nov 2015, at 15:41 pm, Zoltan Botta-Dukat
> wrote:
>
> Dear Moses,
>
> Vegdist s
dissimilarities using specified distance= method
(defaults “euclidean”). You should verify that the selected distance= method is
the one you need. The variables on the right-hand-side of the formula must be
in “raw” (observations times variables) format. They cannot be distances.
Cheers, Jari Ok
l data frames
for the data= argument, please consider cbind().
cheers, Jari Oksanen
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Probaby the difference is the adjustment: varpart() uses adjusted R-squared,
but rda() output reports unadjusted proportions. RsqureAdj() function gives
both.
Cheers, jari Oksanen
From: R-sig-ecology on behalf of Tim
Richter-Heitmann
Sent: 02 November
volume.ellipsoid function to find the volume. Obviously, these work in 2D.
Cheers, Jari Oksanen
> On 30 Sep 2015, at 17:38 pm, Baldwin, Jim -FS wrote:
>
> One metric for an "average width" that would be quick to calculate might be
> the diameter of a circle that has the sa
Natalie & Zoltan,
I'd be more worried about the effect of outliers on the area of convex hulls.
Here an _ad hoc_ definition of outlier: outlier a single point that has a huge
effect on the area of an enclosing convex hull.
That said, two points are certainly on a line, and three points can be (
-metric transformation is made to optimize the
goodness of fit to Euclidean ordination space.
Cheers, Jari Oksanen
On 16/07/2015, at 22:19 PM, Kate Boersma wrote:
> Hi all.
>
> I have a methodological question regarding non-metric multidimensional
> scaling. This is not specific to R.
the latest vegan also adds
similar slope calculations for analytic species accumulation models ("exact",
"rarefaction", "coleman") plus all non-linear regression models in
fitspecaccum() (function specslope()).
Cheers, Jari Oksanen
On 11/05/2015, at 12:09 PM, Jari O
, evaluate at 126 individuals
y <- rarefy(mite[1,], 126) # 19.47011
b <- rarederatk(mite[1,], 126) # derivetive 0.04032 (with warnings)
abline(y-126*b, b) # matches the rarecurve plot
Cheers, Jari Oksanen
From: R-sig-ecology on behalf of Zoltan
mpling units. Several other packages have several other functions that do the
same, almost the same, similar or completely different things loosely
associated with rarefaction.
Cheers, Jari Oksanen
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ll be merged and included in the next
vegan release.
Thanks for reporting this.
Best wishes, Jari Oksanen
From: R-sig-ecology on behalf of
Christoph Eberhard Freiherr von Redwitz
Sent: 05 March 2015 15:29
To: R-sig-ecology@r-project.org
Subject: [R-sig-eco]
Alex,
It is possible that the documentation in vegan answers this. You can try
vegandocs("decision") and go to chapter "Scaling in redundancy analysis" that
also applies to capscale results.
Cheers, Jari Oksanen
From: R-sig-e
ike they used to say).
If you only want to get summaries, check function meandist in vegan.
Cheers, Jari Oksanen
On 13/12/2014, at 02:17 AM, Kate Boersma wrote:
> Hi all.
>
> I have a community analysis data manipulation puzzle for you... hopefully
> someone can help.
Negative values of what? If it is AIC, it is not a problem. With AIC, only
differences are meaningful. The observed values can be negative.
Cheers, Jari Oksanen
Sent from my iPad
> On 29.11.2014, at 19.56, Manoeli Lupatini wrote:
>
> Dear all,
>
> I am working with radfi
more data if you wish to use this tool.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org
on behalf of Rich Shepard
Sent: 21 November 2014 00:08
To: r-sig-ecology@r-project.org
Subject: [R-sig-eco] Minimum Number of Observations for pcaCoDa?
e I understood your data correctly. It looks like you have
a certain number of animals, but their number is reduced with age so that you
have a kind of censored data (animals not available in all cases). Perhaps
somebody can propose a better analysis for such a censored data, if it is like
that.
C
ly or "significantly" ordered and trick you to think that a
linear regression would be a good solution. With five datum points you just
can't know.
Cheers, Jari Oksanen
PS. I hope this threading pleases Gav -- this certainly hurts all Outlook users.
>
>
>
> > Mess
el could be possible if your data points are not single
observations but means from several observations. That is true: then you can
proceed, but consult a statistician on the way to proceed.
Cheers, Jari Oksanen
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It uses the number of columns in the *model* matrix. Factors get expanded into
contrasts in the model matrix: a p-level factor will be expanded into p-1
columns in the model matrix.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org
on
modified to cope with
one-member groups. You can install the modified version of vegan for Windows,
or if you have programming tools for other OS's, too, using:
install.packages("vegan", repos="http://R-Forge.R-project.org&qu
exciting for the general public. You may consider contacting the package
maintainers directly.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org
on behalf of Tim Richter-Heitmann
Sent: 13 October 2014 16:49
To: r-sig-ecology@r-project.org
the bottom of that
> page) to add points to an existing nmds.
>
> I'm not convinced that it's a good idea, but I worked with someone who
> needed it to fulfil contract obligations so I wrote it.
>
It looks like a very good idea to me.
Cheers, Jari Oksanen
_
t yet, though (neither in plans). There are
some tricks that may work even with the current code: check Legendre & Legendre
latest edition.
Cheers, Jari Oksanen
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these two together
with 64 levels are able to completely explain everything and anything in these
data: you run out of degrees of freedom.
Sorry for top-posting and bad formatting: this MS Outlook.
cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-proj
misleading. I have tried to spell
out that warning in vegan manual pages, but people seem to ignore those parts
of the text.
cheers, Jari Oksanen
On 28/05/2014, at 20:05 PM, Nicholas J. Negovetich wrote:
> I have a question related to rarefaction of our samples. Unlike all of the
> e
Dear Claire Della Vedova,
It seems that you have searched in many places, except in vegan documentation.
Look at the vignette on Design decisions, section "Scaling in redundancy
analysis".
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-p
of M variables
really are independent. However, this really needs to be taken into account if
M is low. I have no idea how is that in your case.
Cheers, Jari Oksanen
On 13/05/2014, at 15:32 PM, Zbigniew Ziembik wrote:
> I am not sure, but it seems that your problem is related to
> composi
of M variables
really are independent. However, this really needs to be taken into account if
M is low. I have no idea how is that in your case.
Cheers, Jari Oksanen
On 13/05/2014, at 15:32 PM, Zbigniew Ziembik wrote:
> I am not sure, but it seems that your problem is related to
> composi
within adonis code, and bootstrapping is certainly
better. What is sure is that the equations you gave in your message won't work.
I have never used these adonis coefficients, and I have no idea how to use
them, and therefore I don't have any opinion about their use.
Cheers, Jari Oks
ke that. I suggest you check any ook on factor analysis (starting from
Harman 1977, going to Jöreskog, or anything you find in your local library).
Cheers, Jari Oksanen
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Dear Tracy,
You can see if Helene Wagner's mso() in function in vegan satisfies your needs
for analysing spatial dependence. Reference and further description in ?mso.
Cheers, Jari Oksanen
On 02/04/2014, at 00:12 AM, Pinney, Tracy A wrote:
> Hello List,
>
> I have two questi
huffle for each CV
k <- sample(k)
## the next line could be broken into several commands within {}
for(i in 1:5) x[k==i,] <- calibrate(rda(decostand(mite, "hell") ~
SubsDens+WatrCont, mite.env, subset = k != i), newdata = decostand(mite[k==i,],
"hell"))
Easy, but not very good
Patches welcome. It is best to use vegan in GitHub.
Pairwise tests are not high on my TODO list, because they are so much against
what I've learnt from statistical theory and I detest tests.
Cheers, Jari Oksanen
Sent from my iPad
> On 27.3.2014, at 17.54, "Gavin Simpson&quo
Except that t-test does not assume that *observations* are normally
distributed, nor that variances are equal.
Avoid non-parametric tests: they assume too much of data properties.
For var.equal assumption in t.test, see ?t.test.
Cheers, Jari Oksanen
ou intend to use these in subsequent analysis,
please note that labdsv functions at least seem to assume that data are
non-negative, but it does not check this.
Cheers, Jari Oksanen
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be negative) or straightforward residuals (which
have an average of zero and some of which are negative).
Cheers, jari Oksanen
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the current function
does not return information for getting residuals. Neither would they be
residuals in the traditional meaning of the word as we are dealing with
dissimilarities or distances, and these cannot be negative. We got to discuss
this with vegan developers.
Cheers,
details, this is a blind watchmaker recommendation.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org [r-sig-ecology-boun...@r-project.org]
on behalf of Ivailo [ubuntero.9...@gmail.com]
Sent: 26 February 2014 16:23
To: Rajendra Mohan panda
Cc: r-sig
ing of species 3 hardly influences
the results, and the species is not influential. By far the most important
species is number 1.
Cheers, Jari Oksanen
On 19/02/2014, at 06:10 AM, Vindoggy ! wrote:
>
>
> I have a data set for benthic cover made up of 4 species, over 9 years. I
&g
in question is about this plot, in the plot only we see the
> hydrobiological variables, is there any way or code in plot that also show
> the names of zooplankton groups?
>
Dear Mahnaz Rabbaniha,
Have you tried plot(vare.cca, type="t")?
Cheers, Jari Oksanen
_
rences in AIC/BIC, there is not much difference in the
models (and often even the curves look similar although they are found with
different model equations). You better read on model selection with AIC/BIC.
Cheers, Jari Oksanen
> I copy here the new results:
>
> Cluster I
> RAD mode
people claim that you can use neither deviance nor AIC (and they
are right). At least you must take into account the number of estimated
parameters that varies from zero to three.
Cheers, Jari Oksanen
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Function meandist() should do this. Its name is kind of hint.
Cheers, Jari Oksanen
On 16/12/2013, at 21:16 PM, Andres Mellado Diaz wrote:
> Dear list memnbers,
>
> I would greatly appreciate any suggestion on how to get averaged distance
> values (and errors) between groups of s
e. If there are some other problems, I want to fix them, too. Therefore I
really want to know what happened with your application. I try to reproduce
your problems, but this is kind of blind watchmaker's works as I don't have a
reproducible test case. Therefore I have to ask stubbornly
and either cast character strings to factors or ignore variables that are
neither numeric nor factors.
Cheers, Jari Oksanen
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It is easy if you have C and Fortran compilers plus unix tools. I assume most
people do not have those. Then 'easy' is quite different a concept.
Cheers, Jari Oksanen
alkuperäinen viesti
Lähettäjä: Hadley Wickham
Lähetetty: 05.12.2013, 16:19
Vastaanottaja: Eduard Szöcs
Ko
more info and a *reproducible*
example. We haven't got any now, and I cannot reproduce your problem.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org [r-sig-ecology-boun...@r-project.org]
on behalf of Stephen Sefick [sas0...@auburn.edu]
Se
higher R2 than
dist(y) ~ dist([x1,x2]) -- bioenv is based on this.
Cheers, Jari Oksanen
Sent from my iPad
> On 4.12.2013, at 20.19, "Sarah Goslee" wrote:
>
> Hi,
>
> That seems a bit odd: can you provide a reproducible example, off-list
> if necessary?
>
&
similarity, there is no
information about the original species. You can supply the original community
data (which has the information on species) as argument 'comm' in capscale().
Cheers, Jari Oksanen
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R-si
rnatives are provided for these standard methods. Since the alternatives
are provided, you can study the issue independently.
The existence of a method is not a sufficient reason to use that method.
Cheers, Jari Oksanen
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e a bit easier to write.
Cheers, Jari Oksanen
On 01/11/2013, at 15:53 PM, Philipp01 wrote:
> Hello all,
>
> I would like to cross validate my rda() derived model with the calibrate
> function (vegan package) and calculate the RMSE as value for performance
> measure.
> For
If you use these, remember that R cos() needs argument in radians.
Cheers, Jari Oksanen
Sent from my iPad
> On 18.10.2013, at 8.40, "Ivailo" wrote:
>
>> On Fri, Oct 18, 2013 at 6:16 AM, Michael Marsh wrote:
>>
>> If you want a measure of exposure
rmal usage of RDA let us compare the following cases:
library(vegan)
data(varespec, varechem)
mod <- rda(varespec ~ Al + P + K, varechem)
## gives unadjusted R2=0.377
envfit(mod ~ Al + P + K, varechem, display="lc", choices=1:3)
## **should** give for all vars r2=1 because they were the con
l. If
you really *know* that you need non-centred RDA. then you know how to change
those lines of code in rda.default.
Cheers, Jari Oksanen
From: Paolo Piras [paolo.pi...@uniroma3.it]
Sent: 03 October 2013 15:52
To: Jari Oksanen; r-sig-ecology@r-projec
to have?, (2) how many things would it break by returning several values
instead of one?
If you want to have this, you really do not need to use vegan.
vegan:::RsquareAdj.lm() takes its results from summary(). You can
use that stats:::summary.lm directly.
Cheers, Jari Oksanen
__
2.1-36). But you
really need to to specify a quantitative null model. Both null models and
oecosimu are completely re-written and re-designed in development versions.
Cheers, Jari Oksanen
On 25/09/2013, at 15:56 PM,
wrote:
> Thank you very much. Yes it is working with oecosimu, exep
.
Cheers, Jari Oksanen
alkuperäinen viesti
Lähettäjä: Mitchell, Kendra
Lähetetty: 31.07.2013, 02:38
Vastaanottaja: ""
Aihe: [R-sig-eco] subsetting lower triangle distance matrix based on variable
in another object
I have a number of dissimilarity matrices built in another progra
In some cases lousy email system mandates promoting piracy: i replys, the
previous messages are treated as appendices that cannot be edited. This also
means that you must top-post. Kudos goes to MicroSoft + Nokia.
Cheers, Jari Oksanen
alkuperäinen viesti
Lähettäjä: THIOULOUSE JEAN
need scaling to see
shades of colours. Names can also be unreadable in large tables. Fixes are
welcome. I think ade4 may have something similar.
Cheers, Jari Oksanen
alkuperäinen viesti
Lähettäjä: Basil Iannone
Lähetetty: 24.07.2013, 14:57
Vastaanottaja: Sarah Goslee
Kopio: r-sig
sage to know
what happens.
Do you have missing values in betasim.sim? Are betasim.sim really
dissimilarities?
BTW, vegan has Simpson dissimilarity: use betadiver(x, "sim").
Cheers, Jari Oksanen
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een groups of variables. Vegan functions
do not ignore those.
Cheers, Jari Oksanen
--
Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
jari.oksa...@oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa
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R-sig-ec
ing is that the non-R
software with such tests makes separate pairwise tests using subsets of data
with only two levels of a factor in one tests. We don't provide that in vegan
and have no plans to provide this in the future.
Cheers, Jari Oksanen
--
Jari Oksanen, Dept Biology
ve no residual variation which indicates
that the number
of predictor variables (constraints) is higher than the number of remaining
observations.
Cheers, Jari Oksanen
> So, I am thinking that examining the relationship between the microbial
> community and this subset of environment
On 01/06/2013, at 05:20 AM, Jari Oksanen wrote:
>>
>> The CCA seems to run just fine, but when I attempt to do the posthoc tests
>> such as anova.cca (anova(toolik250.cca,by='terms',perm=999), I get an error
>> message: "Error in anova.ccabyterm(object, st
s to do that,
and that is not difficult: just search for imputation in R (for instance,
package mice). However, the real problem is how to compare and summarize the
multivariate results after imputation. Further, if you have a lot of missing
values, nothing may be very reliable. It could b
Fernando,
For background reading you may check
Stevens. M.H.H. (2009) A Primer of Ecology with R. Use R! Series. Springer.
and associated 'primer' package in CRAN. The book discusses functional
responses.
Cheers, Jari Oksanen
From: r-sig-ec
, significances) for single
terms, but your description sounds like this is not the case.
cheers, Jari Oksanen
On 27/05/2013, at 10:21 AM, Alan Haynes wrote:
> Thanks Jari.
>
> Perhaps I can pose my question slightly differently. In the example I gave
> using the dune data, there is
are easier way of
doing the same. For instance, you seem to want to have sum contrasts, but with
different baseline level. Check functions like model.matrix, contrasts,
relevel, and as.data.frame. However, the magnitude of coefficient also depends
on specific contrasts that you use.
Cheers, Ja
quation than this one here with some mix up with 'n'
and 'p'. The designdist() function calculates (dis)similarities between rows.
You must transpose (t()) your data if you want to have dissimilarities between
columns. The code is pure R so that you can see how to do these cal
e for NMDS from
the very beginning. That is, form 1960s.
Cheers, Jari Oksanen
From: r-sig-ecology-boun...@r-project.org [r-sig-ecology-boun...@r-project.org]
on behalf of Erin Nuccio [enuc...@gmail.com]
Sent: 24 April 2013 12:30
To: r-sig-ecology@r-project.org
urn on 'noshare'
argument in metaMDS to trigger step across dissimilarities. We claim that this
rarely necessary with the monoMDS engine we use currently, but sometimes it is
needed.
Without hands on your data it is difficult to guess more.
Cheers, Jari Oksanen
Sent from my iPa
monotonic regression from *metric* ordination to any
dissimilarity measure. So NMDS finds metric solution from any dissimilarity
measure.
I
--
Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
jari.oksa...@oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa
___
E = 27)
coordinates(xy) <- ~ E + N
proj4string(xy) <- CRS("+proj=longlat")
spTransform(xy, CRS("+init=epsg:3067"))
and it is really useful to validate the results...
Cheers, Jari Oksanen (Finland)
> -Oorspronkelijk bericht-
> Van: r-sig-ecology-boun...@r-proj
s.
If 'd' are your distances, see what does class(d) say. If says "dist" (possibly
with some other alternatives), you are safe. If your 'd' are not of class
"dist", you can try if as.dist(d) changes them to "dist".
Cheers, Jari Oksanen
ngle files from R-Forge, or you can install devel
version of vegan with
install.packages("vegan", repos="http://r-forge.r-project.org";)
It will take a day at minimum to get the version packaged in R-Forge.
Cheers, Jari Oksanen
On 26 Feb 2013, at 3:49, Sarah Loboda wrote:
&
is labels are also suppressed. You can later use
box()
to frame the empty graph if needed.
Cheers, Jari Oksanen
On 26 Feb 2013, at 3:49, Sarah Loboda wrote:
> Hi,
> Here's the reproducible example that I made with dune data. When you do the
> 4 graphs, you can see that because of
ula) <- .BiodiversityR
data1 <- data
assign("data1",data,envir=.BiodiversityR)
model <- capscale(formula,data1,distance="euclidean")
Cheers, Jari Oksanen
On 23/02/2013, at 17:29 PM, Baldwin, Jim -FS wrote:
> I suspect it must be a version problem. Runni
Kay,
This should not work if the function is correctly written. You say that the
terms in your formula are in data=env, but there are no variables env$NFac and
env$Fac in env -- but there are NFac and Fac.
Cheers, Jari
Sent from my iPad
On 23.2.2013, at 12.15, "Kay Cichini" wrote:
> Hi all,
ons") will open up the vignette of the
permute package for your inspection, and this will give some examples of
defining restricted permutations. At some timeframe we are completely moving
to the permute package, but you can already use its permutation matrices as
input with these new and u
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