References

1

Friedman, J. (1987). Exploratory projection pursuit. Journal of the American Statistical Association, 82:249-266.

2

Friedman, J. and Tukey, J. (1974). A projection pursuit algorithm for exploratory data analysis. IEEE Transaction on Computer, c-23(9):881-890.

3

Gnanadesikan, R. and Wilk, M. (1969). Data analytic methods. In Krishnaiah, P., editor, Multivariate Analysis II, pages 593-638. Academic Press.

4

Hall, P. (1989). On polynomial-based projection indices for exploratory projection pursuit. Annals of Statistics, 17:589-605.

5

Hastie, T. and Stuetzle, W. (1989). Principal curves. Journal of the American Statistical Association, 84:502-516.

6

Huber, P. (1985). Projection pursuit (with discussion). Annals of Statistics, 13:435- 475.

7

Iwasaki, M. (1991). Projection pursuit: the idea and practice (in japanese). Bulletin of the Computational Statistics of Japan, 4(2):41-56.

8

Jones, M. C. and Sibson, R. (1987). What is projection pursuit? (with discussion). Journal of the Royal Statistical Society, Series A, 150:1-36.

9

Keren, D., Cooper, D., and Subrahmonia, J. (1994). Describing complicated objects by implicit polynomials. IEEE Transaction on Pattern Analysis and Machine Intelligence, 16(1):38-53.

10

Koyama, K., Morita, A., Mizuta, M., and Sato, Y. (1998). Projection pursuit into three dimensional space (in japanese). The Japanese Journal of Behaviormetrics, 25(1):1-9.

11

Li, K. (1991). Sliced inverse regression for dimension reduction. Journal of the American Statistical Association, 86:316-342.

12

Mizuta, M. (1983). Generalized principal components analysis invariant under rotations of a coordinate system. Journal of the Japan Statistical Society, 14:1-9.

13

Mizuta, M. (1995). A derivation of the algebraic curve for two-dimensional data using the least-squares distance. In Escoufier, Y., Hayashi, C., Fichet, B., Ohsumi, N., Diday, E., Baba, Y., and Lebart, L., editors, Data Science and Its Application, pages 167-176. Academic Press, Tokyo.

14

Mizuta, M. (1996). Algebraic curve fitting for multidimensional data with exact squares distance. In Proceedings of IEEE International Conference on Systems, Man and Cybernetics, pages 516-521.

15

Mizuta, M. (1997). Rasterizing algebraic curves and surfaces in the space with exact distances. In Progress in Connectionist-Based Information Systems -Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, pages 551-554.

16

Mizuta, M. (2002). Relative projection pursuit. In Sokolowski, A. and Jajuga, K., editors, Data Analysis, Classification, and Related Methods, page 131. Cracow University of Economics.

17

Nason, G. (1995). Three-dimensional projection pursuit (with discussion). Applied Statistics, 44(4):411-430.

18

Taubin, G. (1991). Estimation of planar curves, surfaces, and nonplanar space curves defined by implicit equations with applications to edge and range image segmentation. IEEE Transaction on Pattern Analysis and Machine Intelligence, 13(11):1115-1138.

19

Taubin, G. (1994). Distance approximations for rasterizing implicit curves. ACM Transaction on Graphics, 13:3-42.

20

Taubin, G., Cukierman, F., Sullivan, S., Ponce, J., and Kriegman, D. (1994). Parameterized families of polynomials for bounded algebraic curve and surface fitting. IEEE Transaction on Pattern Analysis and Machine Intelligence, 16(3):287-303.