[R-sig-Geo] 4. R from cgi and Xvfb (G. Allegri)
G. Allegri
giohappy at gmail.com
Wed Jan 16 14:15:15 CET 2008
Thanks Marcelo,
I've tried using the suexec module in apache2 (it permits to change
userid and groupid on the base of the scripts called), but from
documentation appears to work only for CGI and SSI, not with
mod_python.
So, I change mailing-list, since the problem is almost OT now in this one :-)
Giovanni
2008/1/16, Marcelo Oliveira <moliveira at geostats.com>:
> Giovanni,
>
> This issue could be related to user permissions. See if you can get
> Apache running under a user with display access rights.
>
> Good Luck,
>
> Marcelo
>
> -----Original Message-----
> From: r-sig-geo-bounces at stat.math.ethz.ch
> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of
> r-sig-geo-request at stat.math.ethz.ch
> Sent: Wednesday, January 16, 2008 6:00 AM
> To: r-sig-geo at stat.math.ethz.ch
> Subject: R-sig-Geo Digest, Vol 53, Issue 14
>
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> Today's Topics:
>
> 1. Re: Spatially Constrained Clustering (Elias T. Krainski)
> 2. regression kriging in gstat with skewed distributions (G. Allegri)
> 3. I Would Dream (vacates at patiencegroup.com)
> 4. R from cgi and Xvfb (G. Allegri)
> 5. Re: regression kriging in gstat with skewed distributions
> (Tomislav Hengl)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 15 Jan 2008 10:51:48 -0300 (ART)
> From: "Elias T. Krainski" <eliaskrainski at yahoo.com.br>
> Subject: Re: [R-sig-Geo] Spatially Constrained Clustering
> To: r-sig-geo at stat.math.ethz.ch
> Message-ID: <569895.79461.qm at web50604.mail.re2.yahoo.com>
> Content-Type: text/plain; charset=iso-8859-1
>
> Hello Carson,
>
> See the SKATER software at
> http://www.est.ufmg.br/leste/skater.htm
> The SKATER is a Spatial 'K'luster Analisys by Tree
> Edge Removal. In future, this method also be available
> in R.
>
> Best,
> Elias.
>
> --- Carson Farmer <cfarmer at uvic.ca> escreveu:
>
> > Hello List,
> >
> > I am trying to find an R package that will
> > accommodate spatially
> > constrained clustering. While I have been unable to
> > find a package that
> > is explicitly designed to do spatially constrained
> > clustering, I was
> > wondering if anyone had found a package that would
> > do constrained
> > clustering of any kind, and adapted this to spatial
> > constraints?
> > I have searched the R site extensively, and googled
> > all night long, but
> > to no avail! I HAVE found this post:
> >
> http://finzi.psych.upenn.edu/R/Rhelp02a/archive/56819.html
> > but the replies did not help much. They lead to
> > several packages which
> > perform spatial clustering (such that significant
> > clusters of say a
> > disease are located within a study region), however,
> > what I would like
> > to do is partition a spatial (grid) dataset based on
> > multiple variables,
> > taking into account their spatial locations (i.e.
> > clustering is based on
> > the variables, but constrained so that clusters are
> > spatially
> > contiguous). I'm thinking mclust is probably the
> > best way to go, but
> > I'm not sure where to start.
> >
> > Any suggestions would be greatly appreciated.
> >
> > Thanks,
> >
> > Carson
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo at stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
>
> Elias T. Krainski
>
>
>
> ------------------------------
>
> Message: 2
> Date: Tue, 15 Jan 2008 15:27:58 +0100
> From: "G. Allegri" <giohappy at gmail.com>
> Subject: [R-sig-Geo] regression kriging in gstat with skewed
> distributions
> To: r-sig-geo at stat.math.ethz.ch
> Message-ID:
> <e12429640801150627q7266a599g77a3df9744edb153 at mail.gmail.com>
> Content-Type: text/plain; charset=WINDOWS-1252
>
> I'm trying to realize e regression kriging with gstat package on my
> soil samples data. The response variable (ECe measuere) and covariates
> appear positvely skewed.
> As Tomislav Hengl suggests in its "framework for RK" [1], a logistic
> transformation is proposed as a generic way to reduce the skeweness by
> using the physical limits of the data.
> Is it really a transformation that can be applied in the generic case
> of skewed datas? I mean,in my case I have non-normal residuals (from
> original data regression), and I'm trying to transform the residuals
> (and not the original values) to do SK on them . Is this approach
> correct?
>
> A related question is how to do normal score transformations (for my
> residuals) in R and gstat. I know gstat doesn't manage transformations
> and back-transformations, so it should be done previously in R... but
> I can't find any package that permit it in a straisghtforward way.
> I've found something with qqnorm(ppoints(data)) and the approx()
> function. Is that all?
>
> Giovanni
>
>
> [1] "A generic framework for spatial prediction of soil variables
> based on regressionkriging" Geoderma 122 (1?2), 75?93.
>
>
>
> ------------------------------
>
> Message: 3
> Date: Tue, 15 Jan 2008 19:25:16 +0100
> From: <vacates at patiencegroup.com>
> Subject: [R-sig-Geo] I Would Dream
> To: r-sig-geo at stat.math.ethz.ch
> Message-ID: <478CFA8C.7030508 at patiencegroup.com>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Kisses Through E-mail http://86.123.21.76/
>
>
>
> ------------------------------
>
> Message: 4
> Date: Wed, 16 Jan 2008 11:04:53 +0100
> From: "G. Allegri" <giohappy at gmail.com>
> Subject: [R-sig-Geo] R from cgi and Xvfb
> To: r-sig-geo at stat.math.ethz.ch
> Message-ID:
> <e12429640801160204h3532ddb9t624b4f6ef658c975 at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
>
> Hi everyone.
> I'm sorry for the question maybe OT.
> I'm trying to use R and Python to run some scripts via web interface.
> I've successfully setup mod_python for Apache and the rpy module.
> R needs X11 to use png() and jpeg() devices, so I have installed Xvfb
> (X virtual framebuffer). I works correctly: if I set the DISPLAY
> variable to point to this X server, rpy can create png files correctly
> from command-line, but it doesn't work when the python script is run
> from web browser.
> I restarted Apache after setting the DISPLAY variable, but the
> Traceback gives me always the same error, about being not able to open
> the X11 device?
>
> Does anyone have made it work right?
> How can tell Apache to run R script and forwarding X requests to my
> Xvfb.
>
> Thanks,
> Giovanni
>
>
>
> ------------------------------
>
> Message: 5
> Date: Wed, 16 Jan 2008 11:08:28 +0100
> From: "Tomislav Hengl" <hengl at science.uva.nl>
> Subject: Re: [R-sig-Geo] regression kriging in gstat with skewed
> distributions
> To: "'G. Allegri'" <giohappy at gmail.com>
> Cc: r-sig-geo at stat.math.ethz.ch
> Message-ID: <001401c85827$bdac65a0$3a871291 at pcibed193>
> Content-Type: text/plain; charset="windows-1250"
>
>
> Dear Giovanni,
>
> Logit transformation can be automatically applied to any variables which
> has a lower and upper
> physical limits (e.g. 0-100%). In R, you can transform a variable to
> logits by e.g.:
>
> > points = read.dbf("points.dbf")
> > points$SANDt = log((points$SAND/100)/(1-(points$SAND/100)))
>
> After you interpolate your variable, you can back-transform the values
> by using:
>
> > SAND.rk = krige(fsand$call$formula, points[sel,], SPC, sand.rvgm)
>
> > SAND.rk$pred=exp(SAND.rk$var1.pred)/(1+exp(SAND.rk$var1.pred))*100
>
> The prediction variance can not be back-transformed, but you can use the
> normalized prediction
> variance by dividing it with the sampled variance. See also section
> 4.2.1 of my lecture notes
> (http://geostat.pedometrics.org/).
>
> There are many transformations that can be applied to force a normality
> of your target variable (see
> e.g. http://en.wikipedia.org/wiki/Data_transformation_(statistics) ).
> The most generic
> transformation is to work with the probability density function values
> (see e.g.
> http://dx.doi.org/10.1016/j.jneumeth.2006.11.004 ), this way you do not
> have to think about how the
> histogram looks at all. But then the interpretation of the regression
> plots becomes rather
> difficult.
>
> In any case, you should apply the transformation already to the target
> variable because also a
> requirement for linear regression is that the residuals are normally
> distributed around the
> regression line.
>
>
> see also:
> FITTING DISTRIBUTIONS WITH R (by Vito Ricci)
> http://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf
>
>
> Tom Hengl
> http://spatial-analyst.net
>
>
> -----Original Message-----
> From: r-sig-geo-bounces at stat.math.ethz.ch
> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of
> G. Allegri
> Sent: dinsdag 15 januari 2008 15:28
> To: r-sig-geo at stat.math.ethz.ch
> Subject: [R-sig-Geo] regression kriging in gstat with skewed
> distributions
>
> I'm trying to realize e regression kriging with gstat package on my
> soil samples data. The response variable (ECe measuere) and covariates
> appear positvely skewed.
> As Tomislav Hengl suggests in its "framework for RK" [1], a logistic
> transformation is proposed as a generic way to reduce the skeweness by
> using the physical limits of the data.
> Is it really a transformation that can be applied in the generic case
> of skewed datas? I mean,in my case I have non-normal residuals (from
> original data regression), and I'm trying to transform the residuals
> (and not the original values) to do SK on them . Is this approach
> correct?
>
> A related question is how to do normal score transformations (for my
> residuals) in R and gstat. I know gstat doesn't manage transformations
> and back-transformations, so it should be done previously in R... but
> I can't find any package that permit it in a straisghtforward way.
> I've found something with qqnorm(ppoints(data)) and the approx()
> function. Is that all?
>
> Giovanni
>
>
> [1] "A generic framework for spatial prediction of soil variables
> based on regressionkriging" Geoderma 122 (1?2), 75?93.
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>
>
> ------------------------------
>
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>
> End of R-sig-Geo Digest, Vol 53, Issue 14
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