Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

Soybeans and the world market [microform] : joint hearing before the Subcommittee on Agricultural Production and Stabilization of Prices and the Subcommittee on Domestic and Foreign Marketing and Product Promotion of the Committee on Agriculture, Nutrition, and Forestry, United States Senate, One Hundredth Congress, second session, on the question of whether the marketing loan program should be expanded to include soybeans, March 18, 1988.

Distributed to some depository libraries in microfiche. Item 1032-C, 1032-D (microfiche)

Cracking the Japanese market [microform] : hearing before the Subcommittee on Trade, Productivity, and Economic Growth of the Joint Economic Committee, Congress of the United States, Ninety-ninth Congress, second session, February 10, 1986.

CIS Microfiche Accession Numbers: CIS 87 J841-9

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Joint municipal and industrial wastewater treatment in rural communities : simulation analysis with poultry processing plants /

Issued Mar. 1980.

A simulation analysis of the market effect of the Australian Broadcasting Corporation

In this paper we utilise a stochastic address model of broadcast oligopoly markets to analyse the Australian broadcast television market. In particular, we examine the effect of the presence of a single government market participant in this market. An examination of the dynamics of the simulations demonstrates that the presence of a government market participant can simultaneously generate positive outcomes for viewers as well as for other market suppliers. Further examination of simulation dynamics indicates that privatisation of the government market participant results in reduced viewer choice and diversity. We also demonstrate that additional private market participants would not result in significant benefits to viewers.

Energy derivative market and derivative pricing via simulation

The deregulation of power industry worldwide has delivered the efficiency gains to the society; meanwhile, the intensity of competition has increased uncertainty and risks to market participants. Consequently, market participants are keen to hedge the market risks and maintain a competitive edge in the market; and this is a good explanation to the flourish of electricity derivative market. In this paper, the authors gave a comprehensive review of derivative contract pricing methods and proposed a new framework for energy derivative pricing to suit the needs of a deregulated electricity market