ADAPTIVE CONTROL THEORY: SURVEY AND POTENTIAL APPLICATIONS TO DECISION PROCESSES*

An important and distinct feature of a class of decision processes discussed in this paper is the possibility of gathering additional information between decisions and using it to improve future decisions. The analysis of these so-called sequential decision processes is both complicated and far-reaching in its implications. The purpose of this paper is to describe this class of decision processes to make its potential both more readily understood and better appreciated.     

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93–113, 2001; J R Stat Soc, Ser B 65:367–389, 2003; Statistics 37:359–363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew–normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763–771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.     

The Impact of Ovarian Cancer on Life Expectancy in Japan

The purpose of this study was to determine how life expectancy is modified by ovarian cancer from 1950-2000. The contributions of ovarian cancer to life expectancy were estimated. The age characteristics of ovarian cancer were detected using the Gompertz relational mortality model. The patterns between years of potential life lost (YPLL) and mortality were obtained by fitting a linear regression equation to the natural logarithm of their ratios. YPLLs are substantially higher in Ireland than in Japan. However, the rates of change were much higher in Japan than in Ireland. YPLLs changed from 0.02 year in 1950 to 0.12 year in 2000. In Japan, there was a sixfold increase in the proportion of YPLLs for death from ovarian cancer relative to those for death from gynaecological cancers during the last half century. The impact of ovarian cancer on life expectancy clearly increased and the age-specific mortality tend to ageing.     

Local influence in null intercept measurement error regression under a student_t model

In this paper we discuss the application of local influence in a measurement error regression model with null intercepts under a Student_t model with dependent populations. The Student_t distribution is a robust alternative to modelling data sets involving errors with longer than Normal tails. We derive the appropriate matrices for assessing the local influence for different perturbation schemes and use real data as an illustration of the usefulness of the application.     

Minimal Basis for a Connected Markov Chain over 3 × 3 ×K Contingency Tables with Fixed Two-Dimensional Marginals

This paper considers a connected Markov chain for sampling 3 × 3 ×K contingency tables having fixed two‐dimensional marginal totals. Such sampling arises in performing various tests of the hypothesis of no three‐factor interactions. A Markov chain algorithm is a valuable tool for evaluating P‐values, especially for sparse datasets where large‐sample theory does not work well. To construct a connected Markov chain over high‐dimensional contingency tables with fixed marginals, algebraic algorithms have been proposed. These algorithms involve computations in polynomial rings using Gröbner bases. However, algorithms based on Gröbner bases do not incorporate symmetry among variables and are very time‐consuming when the contingency tables are large. We construct a minimal basis for a connected Markov chain over 3 × 3 ×K contingency tables. The minimal basis is unique. Some numerical examples illustrate the practicality of our algorithms.     

State space modeling of multiple time series

Time series methods offer the possibility of making accurate forecasts even when the underlying structural model is unknown, by replacing the structural restrictions needed to reduce sampling error and improve forecasts with restrictions determined from the data. While there has been considerable success with relatively simple univariate time series modeling procedures, the complex interrela- tionships possible with multiple series requite more powerful techniques.Based on the insights of linear systems theory, a multivariate state space methos for both stationary and nonstationary problems is described and related to ARMA models. The states or dynamic factors of the procedure are chosen to be robust in the presence of model misspecification, in constrast to ARMA models which lack this property. In addition, by treating th emidel choice as a formal approximation problem certain new optimal properties of the procedure with respect to specification are established; in particular, it is shown that no other model of equal or smaller order fits the observed autocovariance sequence any better in the sense of a Hankel norm. Finally, in the treatment of nonstationary series, a natural decomposition into long run and short run dynamics results in easily implemented two step procedures that use characteristics of the data to identify and model trend and cycle components that correspond to cointegration and error correction models. Applications include annualo U.S. GNP and money stock growth rates, monthly California beef prices and inventories, and monthly stock prices for large retailers.     

Deprivation of Furusato: The damage faced by evacuees after the Fukushima nuclear power plant accident

This paper considers the damage caused by the Great East Japan Earthquake and the meaning of the Fukushima Nuclear Power Plant accident, and reflects on the evacuees' experiences over past 12 years. During this time, several lawsuits demanding the clarification of responsibility for the accident and compensation for damages have been filed against TEPCO (Tokyo Electric Power Company) and the Japanese Government. The “loss and transformation of hometowns (furusato in Japanese)” has become one of the key issues in these lawsuits. While the casees were being litigated, the mandated “evacuation designated zones” were gradually lifted. Even in the “Difficult-to-Return Areas” where annual integrated doses of radioactive substances are over 50 mSv and evacuation orders are still in effect, efforts are being made to lift the evacuation orders. Because they were forced to leave their places of residence, evacuees have claimed, “we lost oue furusato [hometown].” However, because they are able to return after evacuation orders are lifted, both TEPCO and the Japanese Government have insisted that “their furusato has not been lost” and “they cannot claim compensation for furusato damages.” In this paper, I call the irreversible and absolute damage caused by the nuclear power plant accident “the deprivation of furusato.” I look at furusato from three aspects: the relationship between people and nature, the connection between people, and notions of persistence and sustainability. Then, I discuss what kind of reconstruction is being promoted to respond to the deprivation of furusato and for whom.