Statistical models for e-learning data

Statistical Methods and Applications

Volumn 18, Issue 2, 2009, Pages 293-304

  Figini, Silvia ^a   Giudici, Paolo ^a  

^a UNIVERSITY OF PAVIA   (Italy)

Author keywords

E learning data; Nonparametric statistical methods; Predictive models

Indexed keywords

EID: 67349227146     PISSN: 16182510     EISSN: 1613981X     Source Type: Journal    
DOI: 10.1007/s10260-008-0098-4     Document Type: Article

References (18)

1. Azzalini A, Bowman AW (1997) Applied smoothing techniques for data analysis. Oxford Statistical Science Series, Oxford
2. S Bjerve K Doksum 1993 Correlation curves measures of association as functions of covariate values Ann Stat 21 890 902
3. AW Bowman 1984 An alternative method of cross validation for the smoothing of density estimates Biometrika 711 353 360
4. K Doksum S Blyth E Bradlow XL Meng H Zhao 1994 Correlation curves as local measures of variance explained by regression J Am Stat Assoc 89 571 582 (Pubitemid 24792567)
5. Fan J, Gijbels I (1996) Local polynomial modelling and Ist applications. Chapman Hall, London
6. Giudici P (2003) Applied data mining. Wiley, London
7. Green PJ, Silverman BW (1994) Nonparametric regression and generalized linear models: a roughness penality approach. Chapman Hall, London
8. Hastie TJ, Tibshirani RJ (1990) Generalized additive models. Chapman Hall, London
9. MC Jones JS Marron SJ Sheather 1996 A brief survey of bandwidth selection for density estimation J Am Stat Assoc 91 401 407 (Pubitemid 126353404)
10. M Rosenblatt 1956 Remarks on some noparametric estimates of a density function Ann Math Stat 27 832 837
11. M Rudemo 1982 Empirical choice of histograms and kernel density estimators Scand J Stat 9 65 78
12. Scott DW (1992) Multivariate density estimation: theory, practice and visualisation. Wiley, New York
13. DW Scott G Terrell 1987 Biased and unbiased cross validation in density estimation J Am Stat Assoc 82 1131 1146
14. SJ Sheather MC Jones 1991 A reliable data based bandwidth selection method for kernel density estimation J R Stat Soc Ser B 53 683 690
15. Simonoff JS (1996) Smoothing methods in statistics. Springer, New York
16. MA Stone 1974 Cross validatory choice and assessment of statistical predictions J R Stat Soc Ser B 36 111 147
17. CC Taylor 1989 Boostrap choice of the smoothing parameter in kernel density estimation Biometrika 36 111 147
18. Wand MP, Jones MC (1995) Kernel smoothing. Chapman Hall, London