Proceedings of the International Conference on Linear Statistical Inference LINSTAT ’93

Chapter 1 Increments for (CO)Kriging with Trend and Pseudo-Covariance Estimation

Chapter 2 On the Representation of the Minimax Linear Estimator in the Convex Linear Model

Chapter 3 Estimation of Parameters in a Special Type of Random Effects Model

Chapter 4 Recent Results in Multiple Testing: Several Treatments vs. A Specified Treatment

Chapter 5 Multiple-Multivariate-Sequential T 2 -Comparisons

Chapter 6 On Diagnosing Collinearity-Influential Points in Linear Regression

Chapter 7 Using Nonnegative Minimum Biased Quadratic Estimation for Variable Selection in the Linear Regression Model

Chapter 8 Partial Least Squares and a Linear Model

Chapter 9 One-Way Analysis of Variance Under Tukey Contamination: A Small Sample Case Simulation Study

Chapter 10 A Note on Robust Estimation of Parameters in Mixed Unbalanced Models

Chapter 11 Optimal Bias Bounds for Robust Estimation in Linear Models

Chapter 12 Geometrical Relations Among Variance Component Estimators

Chapter 13 Asymptotic Efficiencies of MINQUE and ANOVA Variance Component Estimates in the Nonnormal Random Model

Chapter 14 On Asymptotic Normality of Admissible Invariant Quadratic Estimators of Variance Components

Chapter 15 Admissible Nonnegative Invariant Quadratic Estimation in Linear Models with Two Variance Components

Chapter 16 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

Chapter 17 Prediction Domain in Nonlinear Models

Chapter 18 The Geometry of Nonlinear Inference: Accounting of Prior and Boundaries

Chapter 19 General Balance: Artificial Theory or Practical Relevance?

Chapter 20 Optimality of Generally Balanced Experimental Block Designs

Chapter 21 Optimality of the Orthogonal Block Design for Robust Estimation under Mixed Models

Chapter 22 On Generalized Binary Proper Efficiency-Balanced Block Designs

Chapter 23 Design of Experiments and Neighbour Methods

Chapter 24 A New Look into Composite Designs

Chapter 25 Using the Complex Linear Model to Search for an Optimal Juxtaposition of Regular Fractions

Chapter 26 Some Directions in Comparison of Linear Experiments: A Review

Chapter 27 Properties of Comparison Criteria of Normal Experiments

Chapter 28 Characterizations of Oblique and Orthogonal Projectors

Chapter 29 Asymptotic Properties of Least Squares Parameter Estimators in a Dynamic Errors-in-Variables Model

Chapter 30 A Generic Look at Factor Analysis

Chapter 31 On Q-Covariance and its Applications