Re: [R] PCA and % variance explained
I did PCA stuff years there is a thing that is called a scree score
Which will give an indication of the number of PCA's and the variance
explained.
Might want to web search on scree score and PCA.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of pgseye
Sent: Tuesday, September 09, 2008 5:39 AM
To: r-help@r-project.org
Subject: [R] PCA and % variance explained
After doing a PCA using princomp, how do you view how much each
component contributes to variance in the dataset. I'm still quite new to
the theory of PCA - I have a little idea about eigenvectors and
eigenvalues (these determine the variance explained?). Are the
eigenvalues related to loadings in R?
Thanks,
Paul
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[R] Plotting Dendrogram Help Getting Plot to Display Neatly
I have done a cluster analysis doing:
1-clusNorth -hclust(dist(Artorious)^2, method=ward)
2-clusNorth$labels -Artorious$Name ## to show the case names and not
numbers
3-dend1 - as.dendrogram(clusNorth)
4-plot(dend1)
My Dendrogram is now showing the names of my cases in the dataframe on
the x axis
1OMNICELL INC COM
2GETTY IMAGES INC COM
3 INTERCONTINENTALEXCHANGE IN COM
4 OPTIONSXPRESS HLDGS INC COM
5 SUPERIOR WELL SVCS INC COM
6 HCP INC COM
7 SENIOR HSG PPTYS TR SH BEN INT
8 NATIONWIDE HEALTH PPTYS INC COM
9DUKE REALTY CORP COM NEW
10 HEALTH CARE REIT INC COM
11 POWERSHARES QQQ TRUST UNIT SER 1
12 FLEXTRONICS INTL LTD ORD
13 VENTAS INC COM
However with 60 cases the names above are not fitting neatly into plot.
Can someone advice on plot
Parameters to fix the size of dendrogram and see the full names on X
axis?
Thanks.
Neil
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[R] Need Advice with C# Program to Create and Display Cusum Chart
I need to write a C# program to create and display Cusum chart from any
of the packages,
spc, qcc or strucchange.
Issues:
1-The data resides in a MS SQL Database. The C# program will handle
obtaining the data for the requisite types of samples.
Assistance needed on:
1-How can I call the cusum capabilities of any of the above packages
and pass the data to the cusum function and plot?
2-How can from the C# program, obtain the returned data
and display the plotted chart in my C# program?
3- Displaying the chart in the C# program and allowing it to be saved is
important.
Goal is to make this all transparent to my end users.
Each user will have their own instantiation of R on their PC.
Any advice on best approach would be appreciated. I am looking at
Writing R Extensions doc however a jump start or other
References to doing this within the .net framework would be helpful.
Thanks,
Neil
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[R] Need good Reference Material and Reading about Gaussian Copulas
Can anyone advise me on some pratical papers or books
On Gaussian Copulas? Anything in the genre of Copulas Dummies
Would be a help.
As simpe, and approachable with minimal pedantic style.
Thanks,
Neil
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Re: [R] Clustering techniques using R
Maura:
I looked at the scatter plots you sent.
A few thoughts:
1- Patient 3 data has a lot of missing data. This will make
doing a good grouping against your cases an issue.
Missing data is so common and much work has been done in this area.
One can do the trivial approach, forward fill and backward fill the
sample data
thus have same amount of data for all cases.
The more advanced approaches are, Expectation-Maximization algorithm,
a Google search on EM Algorithm will provide you a lot of info.
Another approach is called, Multiple Imputation
(http://www.multiple-imputation.com/).
EM for your type of data appears to be a good solution.
2- Looking at your data, Principal Component Analysis (PCA) appears to
be your best starting point before
clustering. Many books on this subject but start with these simple
links:
http://en.wikipedia.org/wiki/Karhunen-Lo%C3%A8ve_transform
http://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.
pdf
All the methods mentioned above will be in R... PCA, EM.
Finally, there is no one right answer for clustering, I.e. single
linkage, Complete linkage, Ward's Method et al.
It's always particular to the type of data one is analyzing.
Naturally our fellow R community members might have more and better
insights/suggestion! :)
Hope this helps.
Regards,
Neil
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Prof Brian Ripley
Sent: Monday, October 01, 2007 1:37 PM
To: Maura E Monville
Cc: [EMAIL PROTECTED]
Subject: Re: [R] Clustering techniques using R
On Mon, 1 Oct 2007, Maura E Monville wrote:
Now that I've loaded a file into an R data.frame and played with
linear regression until I got a good model, my next step is clustering
using the coefficients of the regression model (I have many files)
Thanks to some R experts' guidelines I could find plenty of
documentation on regression analysis in the contributed section.
Some touch on the concepts of the underlying theory and then show some
worked out examples (extremely useful).
I found nothing so nicely explained and laid out about cluster
analysis with R.
I would appreciate some suggestion about reading on techniques for
clustering using R. Some application examples are very welcome.
Have you looked at MASS (the book, see the FAQ)?
Or the CRAN task views at
http://cran.r-project.org/src/contrib/Views/Cluster.html
http://cran.r-project.org/src/contrib/Views/Multivariate.html
(Clustering is 'unsupervied classification')?
There is a lot of information there.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
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