1 |
Arppe, A. (2012). polytomous: Polytomous logistic regression for fixed and mixed effects. R package version 0.1.4., http://CRAN.R-project.org/package=polytomous.
|
2 |
Choi, S. and Park, C. (2013). An educational tool for regression models with dummy variables using Excel VBA. Journal of the Korean Data & Information Science Society, 24, 593-601.
과학기술학회마을
DOI
ScienceOn
|
3 |
Friedman, J. H. (1991). Multivariate adaptive regression splines (with discussion). The Annals of Statistics, 19, 1-141.
DOI
ScienceOn
|
4 |
Friedman, J. H. and Silverman, B. W. (1989). Flexible parsimonious smoothing and additive modeling (with discussion). Technometrics, 31, 3-39.
DOI
ScienceOn
|
5 |
Hastie, T. J. and Tibshirani, R. J. (1990). Generalized additive models, Chapman and Hall, London.
|
6 |
Kahng, M. (2011). A study on log-density ratio in logistic regression model for binary data. Journal of the Korean Data & Information Science Society, 22, 107-113.
과학기술학회마을
|
7 |
Kahng, M. and Shin, E. (2012). A study on log-density with log-odds graph for variable selection in logistic regression. Journal of the Korean Data & Information Science Society, 23, 99-111.
과학기술학회마을
DOI
ScienceOn
|
8 |
Kahng, M., Kim, B. and Hong, J. (2010). Graphical regression and model assessment in logistic model. Journal of the Korean Data & Information Science Society, 21, 21-32.
과학기술학회마을
|
9 |
Koo, J. and Lee, Y. (1994). Bivariate B-splines in generalized linear models. Journal of Statistical Computation and Simulation, 50, 119-129.
DOI
ScienceOn
|
10 |
Agarwal, G. G. and Studden, W. J. (1980). Asymptotic integrated mean square error using least squares and bias minimizing spline. The Annals of Statistics, 8, 1307-1325.
DOI
|
11 |
Kooperberg, C. (2013). polspline: Polynomial spline routines. R package version 1.1.8., http://CRAN.R-project.org/package=polspline.
|
12 |
Kooperberg, C., Bose, S. and Stone, J. (1997). Polychotomous regression. Journal of the American Statistical Association, 92, 117-127.
DOI
ScienceOn
|
13 |
Lee, S., Sim, S. and Koo, J. (2004). A study on data mining using the spline basis. Communications of the Korean Statistical Society, 11, 255-264.
과학기술학회마을
DOI
ScienceOn
|
14 |
McCullagh, P. and Nelder, J. A. (1989). Generalized linear models, 2nd ed., Chapman and Hall, London.
|
15 |
Priestley, M. B. (1981). Spectral analysis and time series, Academic Press, London.
|
16 |
Shim, J. and Seok, K. (2012). Semiparametric kernel logistic regression with longitudinal data. Journal of the Korean Data & Information Science Society, 23, 385-392.
과학기술학회마을
DOI
ScienceOn
|
17 |
Shim, J. and Seok, K. (2013). GACV for partially linear support vector regression. Journal of the Korean Data & Information Science Society, 24, 391-399.
과학기술학회마을
DOI
ScienceOn
|
18 |
Stone, C. J. (1994). The use of polynomial splines and their products in multivariate function estimation. The Annals of Statistics, 22, 118-171.
DOI
|