[Qgis-user] Principal Component Analysis ?
Benjamin Ducke
benducke at fastmail.fm
Fri Jun 23 13:08:54 PDT 2017
Can you please stop patronizing people?
Please assume that GIS users can tell the
difference between _exploratory_ and _explanatory_
and are well aware of what specific statistical
methods can and cannot achieve. Whether
or not someone abuses statistical flexibility
is not a question that needs to concern
programmers, such as those that are behind
the _absolutely excellent_ R and the
_absolutely brilliant_ research and documentation
that goes with it, and is shared _absolutely freely_,
and in open source form, so that it can be reviewed
and improved (as opposed to closed source, paid-for
software) -- Thank you.
Best,
Benjamin
On 23/06/17 22:13, Falk Huettmann wrote:
> Hi,
>
> thanks but nope:
>
> CANOCO comes from the 1970s and is widely outdated by now,
> and not achieving (much).
> Just a few botanists (=not trained statisticians or coders) still use
> it, if at all.
> It usually asks the wrong questions and
> uses pretty old methods that are widely improved by now,
> e.g. machine learning. It all sits there instead, inference from
> predictions. Many publications on that matter.
> Sorry (any programmer knows it that machine learning performs 'very high').
> Like with LMs, GLMs and AIC, p-values or Bayesian stuff, CANOCO does not
> generalize nor predict so well.
>
> R is free, a hodgepodge of sorts, and thus, the cutting edge stuff does
> NOT all sit in R (high quality swords have a price, sorry).
> It's reality. Google etc are not programmed in R or with R for good reasons.
> Perhaps a certain blend is helpful, agreed, but hardly anything else.
> R packages also tend to suffer from poor conceptual reviews, e.g. what
> for and why ?
>
> Again,
> please be aware about such things.
> Just because it's statistics, coded by your good buddy, freeware, R (or
> QGIS), it's not all
> automatically good; often the opposite is the case.
>
> It's a fact and the crux you deal with here.
> A so-called hijacking by some coders and their mindsets; we saw it many
> times before,
> and it's self-serving.
> CANOCO is a great example for that.
>
> Kind regards
> Falk
>
> Falk Huettmann PhD, Associate Professor
> Uni of Alaska Fairbanks UAF
>
>
>
>
> On Fri, Jun 23, 2017 at 11:56 AM, Nicolas Cadieux
> <nicolas.cadieux at archeotec.ca <mailto:nicolas.cadieux at archeotec.ca>> wrote:
>
> Hi,
>
> I am not at what needs to be analyzed in this case but yes,
> canonical analysis needs to be well understood before being used.
>
> You can go to Pierre Legendre and Louis Legendre, Numerical Ecology,
> for help. P Legendre also has a book on Spatial analysis in R that
> can be found.
>
> Cheers
> Nicolas
>
> P.S.
>
> As far as statistical software, R is unbeatable for cutting edge
> sciences. It is scary because it's a statistical language before
> being a statistical software. But I agree, some statistics are
> implement in GIS software without any thought.
>
> Le 23 juin 2017 à 15:11, Falk Huettmann <fhuettmann at alaska.edu
> <mailto:fhuettmann at alaska.edu>> a écrit :
>
>> Hi there,
>>
>> in my view and if I may comment here:
>> while R is scary (as stated below), so are probably many of the
>> wrapped R packages really,
>> PCAs are even more scary, and their underlying mindsets,
>> and the real horror starts when such things get
>> implemented into 'homebrews' and such tools, or
>> into QGIS and just as point and klick.
>>
>> As a rule, I would highly suggest to stay clear of such efforts
>> and concepts.
>> It's no good science, and not much defendable. Unless well thought
>> out,
>> it harms the product and reputation you want to create.
>> (for a bad example see Krigging in some major commercial GIS...
>> We have seen such things many places).
>>
>> There should first be a good debate about statistics, if pursued
>> as tools in QGIS etc.
>> Arguably, unless it's predictive (for inference etc) it has no
>> much value these days anymore.
>>
>> Agreed,
>> it's a tragedy of our time that such old things still happen, all
>> the time,
>> and in the sciences.
>> But it ain't no good, really, and is no good progress. My word for it.
>>
>> (I also agree that it is good to keep avenues open for such
>> work, as an option and for people who know what they are doing and
>> why; sure.
>> But not more than that. Many bad examples exist all over for decades)
>>
>> Feel free to follow up as needed; kind regards
>> Falk Huettmann
>> Uni of Alaska Fairbanks
>>
>>
>> On Fri, Jun 23, 2017 at 10:57 AM, Nicolas Cadieux
>> <nicolas.cadieux at archeotec.ca
>> <mailto:nicolas.cadieux at archeotec.ca>> wrote:
>>
>> Hi,
>> You can use R for PCA.
>> Use the R Commander package to add a GUI. R can be scary at
>> first.
>> Nicolas
>>
>> Le 23 juin 2017 à 11:03, image [via OSGeo.org
>> <http://OSGeo.org>] <[hidden email]
>> <http:///user/SendEmail.jtp?type=node&node=5325361&i=0>> a écrit :
>>
>>> Good afternoon,
>>>
>>> i'm working on windows with several opensource tools (qgis,
>>> otb, grass...),
>>>
>>> I generated several OTB texture indices. Now, i want to
>>> evaluate the information 's redundancy thanks to a Principal
>>> Component Analysis.
>>>
>>> => Is it possible to do that with some opensource tools (otb?
>>> qgis? grass?) Moreover, I would like set a mask AND set a
>>> spectral subset (in order to ignore some indices bands which
>>> seems "strange" and not relevant to introduce into the process).
>>>
>>> Could you throw light for me?
>>>
>>> In advance, thank you very much for your help.
>>>
>>> Kind regards.
>>>
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>> ?
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--
Dr. Benjamin Ducke
{*} Geospatial Consultant
{*} GIS Developer
Spatial technology for the masses, not the classes:
experience free and open source GIS at http://gvsigce.org
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