R for Statistics

R for Statistics

Volumn , Issue , 2012, Pages 1-297

  Cornillon, Pierre André ^a   Guyader, Arnaud ^a   Husson, François ^a   Jégou, Nicolas ^a   Josse, Julie ^a   Kloareg, Maela ^a   Matzner Løber, Eric ^a   Rouvière, Laurent ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85130963526     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/b11828     Document Type: Book

References (23)

1. Breiman L., Friedman J., Olshen R. and Stone C. (1984). Classification and Regression Trees. Wadsworth & Brooks, Monterey, CA.
2. Clarke G.M. and Cooke D. (2004). A Basic Course in Statistics. Wiley, New York, 5 ed.
3. Collett D. (2003). Modelling Binary Data. Chapman & Hall/CRC, Boca Raton, FL, 2 ed.
4. Devroye L., Györfi L. and Lugosi G. (1996). A Probabilistic Theory of Pattern Recognition. Springer, New York.
5. Faraway J.J. (2005). Linear Models with R. Chapman & Hall/CRC, London.
6. Fox J. and Weisberg S.H. (2011). An R Companion to Applied Regression. Sage Publications, London, 2 ed.
7. Govaert G. (2009). Data Analysis. Wiley, New York.
8. Greenacre M. (2007). Correspondence Analysis in Practice. Chapman & Hall/CRC, Boca Raton, FL.
9. Greenacre M. and Blasius J. (2006). Multiple Correspondence Analysis and related methods. Chapman & Hall/CRC, Boca Raton, FL.
10. Hastie T., Tibshirani R. and Friedman J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York, 2 ed.
11. Hosmer D. and Lemeshow S. (2000). Applied Logistic Regression. Wiley, New York, 2 ed.
12. Husson F., Lê S. and Pagès J. (2010). Exploratory Multivariate Analysis by Example Using R. Chapman & Hall/CRC, London.
13. Jolliffe I. (2002). Principal Component Analysis. Springer, New York.
14. Kaufman L. and Rousseeuw P.J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York.
15. Lebart L., Morineau A. and Warwick K.M. (1984). Multivariate Descriptive Statistical Analysis: Correspondence Analysis and Related Techniques for Large Matrices. Wiley series in probability and mathematical statistics: Applied probability and statistics. Wiley, New York.
16. McLachlan G. (2004). Discriminant Analysis and Statistical Pattern Recognition. Wiley, New York, 2 ed.
17. Moore D.S., McCabe G.P. and Craig B. (2007). Introduction to the Practice of Statistics. Freeman, W. H. & Company, New Zealand, 6 ed.
18. Murrel P. (2005). R Graphics. Chapman & Hall/CRC, New Zealand.
19. Murtagh F. (2005). Correspondence Analysis and Data Coding with R and Java. Chapman & Hall/CRC Press, London.
20. Sahai H. and Ageel M.I. (2000). The Analysis of Variance: Fixed, Random and Mixed Models. Birkhäuser Publisher, Boston, MA.
21. Varmuza K. and Filmozer P. (2009). Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL.
22. Vinzi V., Chin W., Henseler J. and Wang H.e. (2010). Handbook of Partial Least Squares. Springer, Boston, MA.
23. Welch B.L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38, 330–336.