Preface. Estimation, Prediction and Testing in Linear Models. Increments for (co)kriging with trend and pseudo-covariance estimation; L.C.A. Corsten. On the presentation of the minimax linear estimator in the convex linear model; H. Drygas, H. Läuter. Estimation of parameters in a special type of random effects model; J. Volaufová. Recent results in multiple testing: several treatments vs. a specified treatment; C.W. Dunnett. Multiple-multivariate-sequential T2-comparisons; C.P. Kitsos. On diagnosing collinearity-influential points in linear regression; H. Nyquist. Using nonnegative minimum biased quadratic estimation for variable selection in the linear regression model; S. Gnot, H. Knautz, G. Trenkler. Partial least squares and a linear model; D. von Rosen. Robustness. One-way analysis of variance under Tukey contamination: a small sample case simulation study; R. Zielinski. A note on robust estimation of parameters in mixed unbalanced models; T. Bednarski, S. Zontek. Optimal bias bounds for robust estimation in linear models; C.H. Müller. Estimation of Variance Components. Geometrical relations among variance component estimators; L.R. LaMotte. Asymptotic efficiencies of MINQUE and ANOVA variance component estimates in the nonnormal random model; P.H. Westfall. On asymptotic normality of admissible invariant quadratic estimators of variance components; S. Zontek. Admissible nonnegative invariant quadratic estimation in linear models with two variance components; S. Gnot, G. Trenkler, D. Stemann. About the multimodality of the likelihood function when estimating the variance components in a one-way classification by means of the ML or REML method; V.Guiard. Nonlinear Generalizations. Prediction domain in nonlinear models; S. Audrain, R. Tomassone. The geometry of nonlinear inference: accounting of prior and boundaries; A. Pázman. Design and Analysis of Experiments. General balance: artificial theory or practical relevance? R.A. Bailey. Optimality of generally balanced experimental block designs; B. Bogacka, S. Mejza. Optimality of the orthogonal block design for robust estimation under mixed models; R. Zmyślony, S. Zontek. On generalized binary proper efficiency-balanced block designs; A. Das, S. Kageyama. Design of experiments and neighbour methods; J.-M. Azaïs. A new look into composite designs; S. Ghosh, W.S. Al-Sabah. Using the complex linear model to search for an optimal juxtaposition of regular fractions; H. Monod, A. Kobilinsky. Some directions in comparison of linear experiments: a review; C. Stępniak, Z. Otachel. Properties of comparison criteria of normal experiments; J. Hauke, A. Markiewicz. Miscellanea. Characterizations of oblique and orthogonal projectors; G. Trenkler. Asymptotic properties of least squares parameter estimators in a dynamic errors-in-variables model; J. ten Vregelaar. A generic look at factor analysis; M. Lejeune. On Q-covariance and its applications; A. Krajka, D. Szynal. Contributor Index. Subject Index.
Proceedings of the International Conference on Linear Statistical Inference LINSTAT '93
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$194.00
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Preface. Estimation, Prediction and Testing in Linear Models. Increments for (co)kriging with trend and pseudo-covariance estimation; L.C.A. Corsten. On the presentation of the minimax linear estimator in the convex linear model; H. Drygas, H. Läuter. Estimation of parameters in a special type of random effects model; J. Volaufová. Recent results in multiple testing: several treatments vs. a specified treatment; C.W. Dunnett. Multiple-multivariate-sequential T2-comparisons; C.P. Kitsos. On diagnosing collinearity-influential points in linear regression; H. Nyquist. Using nonnegative minimum biased quadratic estimation for variable selection in the linear regression model; S. Gnot, H. Knautz, G. Trenkler. Partial least squares and a linear model; D. von Rosen. Robustness. One-way analysis of variance under Tukey contamination: a small sample case simulation study; R. Zielinski. A note on robust estimation of parameters in mixed unbalanced models; T. Bednarski, S. Zontek. Optimal bias bounds for robust estimation in linear models; C.H. Müller. Estimation of Variance Components. Geometrical relations among variance component estimators; L.R. LaMotte. Asymptotic efficiencies of MINQUE and ANOVA variance component estimates in the nonnormal random model; P.H. Westfall. On asymptotic normality of admissible invariant quadratic estimators of variance components; S. Zontek. Admissible nonnegative invariant quadratic estimation in linear models with two variance components; S. Gnot, G. Trenkler, D. Stemann. About the multimodality of the likelihood function when estimating the variance components in a one-way classification by means of the ML or REML method; V.Guiard. Nonlinear Generalizations. Prediction domain in nonlinear models; S. Audrain, R. Tomassone. The geometry of nonlinear inference: accounting of prior and boundaries; A. Pázman. Design and Analysis of Experiments. General balance: artificial theory or practical relevance? R.A. Bailey. Optimality of generally balanced experimental block designs; B. Bogacka, S. Mejza. Optimality of the orthogonal block design for robust estimation under mixed models; R. Zmyślony, S. Zontek. On generalized binary proper efficiency-balanced block designs; A. Das, S. Kageyama. Design of experiments and neighbour methods; J.-M. Azaïs. A new look into composite designs; S. Ghosh, W.S. Al-Sabah. Using the complex linear model to search for an optimal juxtaposition of regular fractions; H. Monod, A. Kobilinsky. Some directions in comparison of linear experiments: a review; C. Stępniak, Z. Otachel. Properties of comparison criteria of normal experiments; J. Hauke, A. Markiewicz. Miscellanea. Characterizations of oblique and orthogonal projectors; G. Trenkler. Asymptotic properties of least squares parameter estimators in a dynamic errors-in-variables model; J. ten Vregelaar. A generic look at factor analysis; M. Lejeune. On Q-covariance and its applications; A. Krajka, D. Szynal. Contributor Index. Subject Index.
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