Codapack a tool for compositional data analysis
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CoDaPack : A tool for Compositional Data Analysis. M. Comas- Cufí & S. Thió-Henestrosa ( [email protected] ) Dept. Computer Sciences and Applied Mathematics University of Girona ( UdG ) Catalonia-Spain. What’s coda?.

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CoDaPack : A tool for Compositional Data Analysis

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Codapack a tool for compositional data analysis

CoDaPack: A toolforCompositional Data Analysis

M. Comas-Cufí & S. Thió-Henestrosa

([email protected])

Dept. Computer Sciences and Applied Mathematics

University of Girona (UdG)

Catalonia-Spain


What s coda

What’s coda?

We are interested in relative values ; total sum is not informative.

  • Vector x=[x1, x2,…, xD]

  • Add to a constant: 100, 1, 106, 109, …

    • Units: percentage, part per one, ppm, ppb, …

  • Has positive elements

  • Carry only relative information

  • Examples

    • Production (pieces): [Ok, NonOk, Rework] = [87, 1, 12]

    • Household budget (€): [Food, Serv., Other] = [1150, 623, 351]

    • Daily activities (h): [Work, Sleep, Other] = [7.5, 7.5, 9]


Sample space of coda simplex

Sample space of coda: simplex

  • Compositional data live in the simplex (S) represented in ternary (D=3), quaternary (D=4), … diagram

x = [0.45,0.35,0.2]

x=[0.2,0.25,0.2 ,0.35]

D=3

S3

D=4

S4


Euclidean distance appropriate

Euclidean distance appropriate?

B

A

STOP PROD.

HALF PROD.

NON-STOP

PROD.

STOP PROD.

HALF PROD.

NON-STOP

PROD.

A2009= [0.2, 0.1, 0.7]

B2009= [0.4, 0.3, 0.3]

B2010= [0.3, 0.4, 0.3]

A2010= [0.1, 0.2, 0.7]

A2010- A2009= B2010- B2009= [-0.1, 0.1, 0]

de(A)=de(B)=0.14  measures the absolute difference


Euclidean distance appropriate1

Euclidean distance appropriate?

B

A

STOP PROD.

HALF PROD.

NON-STOP

PROD.

NON-STOP

PROD.

STOP PROD.

HALF PROD.

2009

2010

0.1

0.2

0.7

0.7

0.4

0.4

0.3

0.3

0.3

0.1

0.2

0.3

0.7

0.3

0.3

0.4

0.1

0.2

-50%

-25%

+100%

+33.3%

0%

0%


Euclidean distance appropriate2

Euclidean distance appropriate?

STOP PROD.

Our interest lies on relative values

A2010/A2009=[1/2, 2, 1]

B2010/B2009=[3/4, 4/3, 1]

Euclidian distance:

de(A) = de(B) = 0.14

B2009

B2010

A2009

A2010

Aitchisondistance:

da(A)=0.6276

da(B) = 0.3970

HALF PROD.

NON-STOP

PROD.


Classical multivariate normal model appropriate

Classical multivariate normal model appropriate?


Log ratio methodology

Log-ratio methodology

  • Aitchison geometry to CODA is equivalent to classical euclidean geometry to log-ratio values.

Simplex (restricted space)  Real space (non restricted)

[x1,…,xD] log(xi/xj), i,j = 1,…,D, j ≠ i


Codapack 2

CoDaPack 2


Software

Software

CoDaPack: software developed by the Departament of Computer Science and Applied Mathematics in the Universitat de Girona. Easy and intuitive.

http:[email protected]

compositions (R-package): analysis of compositional and positive data using different approaches.

http://cran.r-project.org/ [email protected]

robCompositions (R-package): robust estimation for compositional data

http://cran.r-project.org/ [email protected]


References

References

  • Aitchison, J., 1986. The Statistical Analysis of Compositional Data. Chapman & Hall, London. Reprinted in 2003 with additional material byBlackburn Press.

  • Proceedings of CoDaWork, 2003-2005-2008-2011: available in http://dugi-doc.udg.edu/handle/10256/150.

  • CoDaWeb: Compositional Data Analysis Web Site: http://www.compositionaldata.com/


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