Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

Effect of a new selection procedure on adaptive estimation

Adaptive estimation of parameters of some failure time distributionsis considered. A new procedure named the F-procedure has beendeveloped for selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimatorsof parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptiveestimators by simulation of samples using the Monte Carlo method.Adaptive estimation of parameters of some failure time distributions is considered. A new procedure named the F-procedure has been developedfor selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimators of parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptive estimators by simulation of samples using the Monte Carlo method.     

A property of coefficients of variation for ordered bivariate log-normal variables

This paper considers the maximum and minimum of a pair of log-normal variables with equal mean. It shows that either order statistic has a smaller coefficient of variation than the two original log-normal variables provided the latter are of equal variance. When the variances are unequal, as the variance ratio increases, the minimum (maximum), has a smaller coefficient of variation if the correlation coefficient of the log-normal variables is small (small) and the variances are large (small).     

A generalization of the compound rayleigh distribution: using a bayesian method on cancer survival times

In this paper the generalized compound Rayleigh model, exhibiting flexible hazard rate, is high¬lighted. This makes it attractive for modelling survival times of patients showing characteristics of a random hazard rate. The Bayes estimators are derived for the parameters of this model and some survival time parameters from a right censored sample. This is done with respect to conjugate and discrete priors on the parameters of this model, under the squared error loss function, Varian's asymmetric linear-exponential (linex) loss function and a weighted linex loss function. The future survival time of a patient is estimated under these loss functions. A Monte Carlo simu¬lation procedure is used where closed form expressions of the estimators cannot be obtained. An example illustrates the proposed estimators for this model.     

Contraceptive Responsibility among Male University Students

Abstract

This paper assesses the male contribution to contraceptive mismanagement and unwanted pregnancy. The subjects were 109 students at the University of Melbourne. A high incidence of risk-taking was reported, and almost one-fifth of the sexually experienced men stated that they had been involved in an unwanted pregnancy. A small group of these reported more than one such incident. The underlying reasons for poor contraceptive technique seemed to be related to two beliefs: that contraception is a female responsibility, and that sexual intercourse should be entirely spontaneous and unplanned.     

Human Health Risk Assessment of Penicillin/Aminopenicillin Resistance in Enterococci Due to Penicillin Use in Food Animals

Penicillin and ampicillin drugs are approved for use in food animals in the United States to treat, control, and prevent diseases, and penicillin is approved for use to improve growth rates in pigs and poultry. This article considers the possibility that such uses might increase the incidence of ampicillin-resistant Enterococcus faecium (AREF) of animal origin in human infections, leading to increased hospitalization and mortality due to reduced response to ampicillin or penicillin. We assess the risks from continued use of penicillin-based drugs in food animals in the United States, using several assumptions to overcome current scientific uncertainties and data gaps. Multiplying the total at-risk population of intensive care unit (ICU) patients by a series of estimated factors suggests that not more than 0.04 excess mortalities per year (under conservative assumptions) to 0.14 excess mortalities per year (under very conservative assumptions) might be prevented in the whole U.S. population if current use of penicillin drugs in food animals were discontinued and if this successfully reduced the prevalence of AREF infections among ICU patients. These calculations suggest that current penicillin usage in food animals in the United States presents very low (possibly zero) human health risks.     

The effect of non-normality on estimating the variance of the combined ratio estimate in complex surveys

The performance of the balanced half-sample, jackknife and linearization methods for estimating the variance of the combined ratio estimate is studied by means of a computer simulation using artificially generated non-normally distributed populations.

The results of this investigation demonstrate that the variance estimates for the combined ratio estimate may be highly biased and unstable when the underlying distributions are non-normal. This is particularly true when the number of observations available from each stratum is small. The jack-     

Some Reflections on the Legacies of Michael White: An Australian Perspective

This article, which appears in a special 30‐year anniversary edition of the Australian and New Zealand Journal of Family Therapy, reflects on the legacies of the work of Michael White. It begins by looking back on Michael's time as editor of the Australian Journal of Family Therapy. Of the many themes that were discussed in the Editorials and Letters to the Editor section of this journal in the early 1980s, this article focuses on three in particular to explore the legacies of the work of Michael White. The author describes how Michael has bequeathed not only a profound body of work, but also a distinctive spirit of originating, and ways of working that consider the effects of social issues and that examine the politics of experience. It is the author's hope that this approach to considering Michael White's legacies honours his work and also honours the contributions of the Australian and New Zealand Journal of Family Therapy in its 30th year.     

Pandemic Recovery Analysis Using the Dynamic Inoperability Input-Output Model

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model^{( 1 , 2 )} and the dynamic inoperability input-output model (DIIM).^{( 3 )} These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.