THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Social Network Analysis

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The Theory of Industrial Organization

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Models and algorithms for road network design: a review and some new developments

Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Transportation network analysis

Establishing the performance reliability of a transport network is an important practical problem for engineers and planners involved in network design. Methods proposed hitherto have assumed knowledge of link performance frequency distributions (usually delay, travel time or capacity distributions), information that is in many cases absent. In this paper, a two-player non-cooperative game is envisaged between on the one hand the network user seeking a path to minimise the expected trip cost and on the other hand an “evil entity” choosing link performance scenarios to maximise the expected trip cost. At the Nash mixed strategy equilibrium, the user is unable to reduce the expected trip cost by changing his path choice probabilities while the evil entity is unable to increase the expected trip cost by changing the scenario probabilities, without cooperating. The Nash equilibrium measures network performance when users are extremely pessimistic about the state of the network and may therefore be used as a basis for a cautious approach to network design.

A game theory approach to measuring the performance reliability of transport networks

The Generalised Least Squares (GLS) approach to the estimation of Origin-Destination (OD) matrices permits the combination of survey and traffic count data in a way that allows for the relative accuracy of the two data sources. However, the procedure may result in estimates that infringe non-negativity or other constraints on the fitted values. A simple algorithm to solve the GLS problem subject to inequality constraints is presented and its convergence is proven. Expressions are derived for the variances and covariances of the fitted values both without active constraints. It is demonstrated that the imposition of inequality constraints can improve the accuracy of those fitted values directly and indirectly affected them, by reducing their sensitivity to error in the inputs.

Michael G.H. Bell

Papers

Models and algorithms for road network design: a review and some new developments

Transportation network analysis

A game theory approach to measuring the performance reliability of transport networks

The estimation of origin-destination matrices by constrained generalised least squares

Transportation Network Analysis: Bell/Transportation Network Analysis