Computational Statistics

Volume 10.

(as bibtex)

27 references.

Articles

• 1-8. Perspectives for investigating data of a psychological survey
  Schweizer, Karl
• 113-127. Trellis displays vs. interactive graphics
  Theus, Martin
• 129-141. Bounded-variable least-squares: An algorithm and applications
  Stark, P. B., Parker, R. L.
• 143-154. Computing the error for smoothing splines
  van der Linde, Angelika
• 15-20. Discriminant and cluster analysis
  Wernecke, K.-D.
• 155-175. A shape constrained smoother: Simulation study
  Delecroix, M., Simioni, M., Thomas-Agnan, C.
• 177-192. On the determination of lag order in vector autoregressions of cointegrated systems
  Jacobson, Tor
• 205-231. The fast Monte-Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems (Disc: p233-258)
  Girard, D. A.
• 21-27. Hierarchical cluster analysis
  Fischer, J.
• 233-234. Comment on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems''
  Burman, P.
• 235-238. Comment on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems'' )
  Godtliebsen, F., Rue, H.
• 239-241. Comment on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems''
  Hudson, H. M., Lee, T. C. M.
• 243-248. Comment on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems'' (Corr: 96V11 p87-90)
  Kay, J.
• 249-250. Comment on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems''
  Wahba, G.
• 251-258. Reply to comments on ``The fast Monte Carlo cross-validation and $C_L$ procedures: Comments, new results and application to image recovery problems''
  Girard, D. A.
• 259-283. Minimax estimation of linear functionals, particularly in nonparametric regression and positron emission tomography
  Stander, J., Silverman, B. W.
• 285-298. A nonparametric model for unbalanced longitudinal data with application to geophysical data
  Boularan, J., Ferre, L., Vieu, P.
• 29-36. Look first, then model: Exploring the data using the interactive graphics of PC-ISP
  Huber, Thomas M., Nagel, Matthias
• 299-306. An efficient algorithm for weighted PCA
  Krijnen, W. P., Kiers, H. A. L.
• 311-325. Low-storage quantile estimation
  Hurley, C., Modarres, R.
• 327-338. Efficient implementation of some contextual classification methods
  Flygare, A.-M., Barrlund, A.
• 339-351. A fixed effect curvilinear model
  Besse, P. C., Ferraty, F.
• 353-373. Posterior analysis of stochastic frontier models using Gibbs sampling
  Koop, G., Steel, M. F. J., Osiewalski, J.
• 43-51. Methodological comments relating to the presented classificatory and data-analytic methods
  Bock, Hans H.
• 53-69. A regularization method for one-dimensional edge detection and edge-preserving smoothing
  Cheng, Bing, Kay, Jim
• 71-90. Sensitivity functions and numerical analysis of the repeated median slope
  Hossjer, Ola, Hoessjer, Ola, Rousseeuw, Peter J., Croux, Christophe, Hössjer, Ola
• 9-14. Classification trees
  Vach, W.