Ghosh S. Multivariate Analysis, Design of Experiments,...1999

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Describes recent developments and surveys important topics in the areas of multivariate analysis, design of experiments, and survey sampling. Features the work of nearly 50 international leaders
Sampling designs and prediction methods for Gaussian spatial processes; design techniques for probabilistic sampling of items with variable monetary value; small area estimation -a Bayesian perspective; Bayes sampling designs for selection procedures; cluster coordinated composites of diverse datasets on several spatial scales for designing extensive environmental sample surveys - prospectus on promising protocols; corrected confidence sets for sequentially designed experiments, II -examples; resampling marked point processes; graphical Markov models in multivariate analysis; robust regression with censored and truncated data; multivariate calibration; some consequences of random effects in multivariate survival models; a unified methodology for constructing multivariate autoregressive models; statistical model evaluation and information criteria; multivariate rank tests; asymptotic expansions of the distribution of some test statistics for elliptical populations; a review of variance estimators with extensions to multivariate nonparametric regression models; on affine invariant sign and rank tests in one and two sample multivariate problems; correspondence and component analysis; growth curve models; dealing with uncertainties in queues and networks of queues; optimal Bayesian design for a logistic regression model - geometric and algebraic approaches; structure of weighing mattrices of small order and weight

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