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Ian Michael (admin)
Board Administrator
Username: admin

Post Number: 24
Registered: 1-2006
Posted on Friday, August 21, 2009 - 3:54 am:   

If you're interested in the book, we do have it in stock:

http://www.impublications.com/shop/multivariate-data-analysis-in_practice-5-edition-cd.html

Ian
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Marina Steplyuk (marina)
New member
Username: marina

Post Number: 1
Registered: 8-2009
Posted on Thursday, August 20, 2009 - 6:53 pm:   

Hi Ravi,
I think that it will be very useful if you purchase the �Multivariate Date Analysis in practice� book published by Kim H. Esbensen. The book an introduction to Multivariate Data Analysis and Experimental Design.
I found this book is very good
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iyas (iyas)
Senior Member
Username: iyas

Post Number: 29
Registered: 7-2007
Posted on Thursday, August 20, 2009 - 8:32 am:   

dear ravi
sorry , for this device and this software
i do not have experience
sorry again
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Ravi Kalyanaraman (kalyanar)
New member
Username: kalyanar

Post Number: 2
Registered: 8-2009
Posted on Thursday, August 20, 2009 - 8:02 am:   

Iyas,

I am using Phazir handheld unit with the built in method generator sotfware.
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Z. Imbo (zimbo)
New member
Username: zimbo

Post Number: 1
Registered: 5-2008
Posted on Wednesday, August 19, 2009 - 1:28 am:   

One very helpful explanation of PCA was the following:

say you only have two sets of variables. Put them into a coordinate system as x- and y-values. Move all datapoints so that the center of the cloud becomes 0;0 (by substracting the averages of x and of y). Draw a line between the 2 most distant datapoints. Use this line as PC1 and turn the whole picture, the new x-axis. Use the orthogonal as PC2, because ignoring the first PC this gives you the largest differences now. This becomes the new y-axis.
So this centering and turning can also happen in multiple dimensions, giving you the biggest differences of a set of datapoints as PC1.

See also http://en.wikipedia.org/wiki/Principal_component_analysis#Details

Cheers
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venkatarman (venkynir)
Senior Member
Username: venkynir

Post Number: 87
Registered: 3-2004
Posted on Tuesday, August 18, 2009 - 11:52 pm:   

Dear Ravi;
We will welcome you!
PCA defined as "Eigen Analysis to huge matrix of co-varaince or co-relation to project optimum value matrix".It is nothing but decompose of matrix in three part.
mXn =(m xp)x(Pxq)x(qxn)
first one is called as score
second one called eigen
combinationof second ands third on is called as loading.
Please Down load"R language" and read I feel you find answer for your questions.
venkynir -India
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iyas (iyas)
Senior Member
Username: iyas

Post Number: 28
Registered: 7-2007
Posted on Tuesday, August 18, 2009 - 3:39 pm:   

dear ravi
what kind of nir device you use and do you use any kind of software like for multivariate analysis like camo , etc
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Ravi Kalyanaraman (kalyanar)
New member
Username: kalyanar

Post Number: 1
Registered: 8-2009
Posted on Tuesday, August 18, 2009 - 10:01 am:   

I am new to NIR and would like to know the following: What is the exact step by step procedure used in the PCA process? I understand that the spectral data after pretreatment is taken in a matrix form and mathematically transformed to get the PC scores, but would like to know the exact procedure. For example, is the first row in the matrix the wavelength or wavenumber data and the second, third and fourth rows the intensity? Thank you for the information.

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