COMPSTAT: Proceedings in Computational Statistics ; 14th Symposium Held in Utrecht, The Netherlands, 2000 ; with 96 TablesJelke G. Bethlehem, Peter G. M. van der Heijden Springer Science & Business Media, 2000 - 540 pages This book contains the keynote, invited and full contributed papers presented at COMPSTAT 2000, held in Utrecht. The papers range over all aspects of the link between statistical theory and applied statistics, with special attention for developments in the area of official statistics. The papers have been thoroughly refereed. |
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... cell suppression software ( CONFID ) ....... ......... 403 D.A. Robertson The multimedia project MM * STAT for teaching statistics . B. Rönz , M. Müller & U. Ziegenhagen 409 Projection pursuit approach to robust canonical correlation ...
... cell suppression software ( CONFID ) ....... ......... 403 D.A. Robertson The multimedia project MM * STAT for teaching statistics . B. Rönz , M. Müller & U. Ziegenhagen 409 Projection pursuit approach to robust canonical correlation ...
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Contents
I | 3 |
II | 15 |
III | 29 |
IV | 41 |
V | 53 |
VI | 65 |
VII | 77 |
VIII | 87 |
XL | 319 |
XLI | 325 |
XLII | 331 |
XLIII | 337 |
XLIV | 343 |
XLV | 349 |
XLVI | 355 |
XLVII | 361 |
IX | 97 |
X | 109 |
XI | 121 |
XII | 131 |
XIII | 139 |
XIV | 151 |
XV | 161 |
XVI | 175 |
XVII | 181 |
XVIII | 187 |
XIX | 193 |
XX | 199 |
XXI | 205 |
XXII | 211 |
XXIII | 217 |
XXIV | 223 |
XXV | 229 |
XXVI | 235 |
XXVII | 241 |
XXVIII | 247 |
XXIX | 253 |
XXX | 259 |
XXXI | 265 |
XXXII | 271 |
XXXIII | 277 |
XXXIV | 283 |
XXXV | 289 |
XXXVI | 295 |
XXXVII | 301 |
XXXVIII | 307 |
XXXIX | 313 |
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Common terms and phrases
aggregate aggregate series algorithm analysis applets application approach approximation asymptotic autoregressive Bayes factor Bayesian bias cells classification cluster coefficients component COMPSTAT computational conditional independence considered correlation corresponding covariance matrix data mining data set database defined denote density dimension distribution EM algorithm error estimation example forecasting function Gibbs sampler given implemented impulse responses interaction intervals item response iterative Jasp Journal Keywords linear models Markov chain maximum likelihood MCMC mean measure methods missing data missing values mixture multiple imputation multivariate nonresponse normal observations obtained optimal outliers paper parameters performance plot points population posterior posterior probability prediction predictor probability problem procedure proposed random regression residuals robust Rousseeuw Rubin rules S-Plus score seasonal adjustment Section selection simulation spatial spline spreadsheet standard Statistics Netherlands step stochastic structure survey Table techniques tree Van Driessen variables variance vector weights