Dengue is one of the most dangerous vector-borne infectious diseases in the world which are fatal in many cases due to inefficient treatment. Although the relative risk estimations of dengue transmission are available for Bandung, one of the most populous cities in Indonesia, dengue cases especiall y among young people have increased rapidly. However, the age factor has not yet been included in these estimations. Because specific treatment and prevention depend on age, this factor must be considered in any dengue transmission model. In this article, the authors classify dengue cases in Bandung into juveniles and adults. Each group is analyzed by SIR-SI model to estimate the relative risk of dengue transmission as an indirect transmission disease which takes into account the stochastic factor. This model also considers a spatial correlation which affects dengue distribution in a specific area for a particular age group. The results of the analysis show that some areas in Bandung have medium to very high dengue risk, especially for the juvenile group. It is expected that The Health Department of Bandung will focus dengue transmission prevention programs more intensively on this group. In further research, if the data needed are available, this model can be applied to other cities in Indonesia.

Twenty exponential type estimators with imputation have been suggested to overcome the problem of missing data for a study variable in sample surveys. It has been shown that the suggested estimators are more efficient than the mean method of imputati

We consider the problem of estimating the parameters of generalized Rayleigh distribution both from frequentist and Bayesian point of view when the available data is in the form of record values. Bayes' estimators of the unknown parameters are obtained under symmetric and asymmetric loss functions using gamma priors on both the shape and the scale parameters. The Bayes estimators cannot be obtained in explicit forms. So we propose Markov Chain Monte Carlo (MCMC) techniques to generate samples from the posterior distributions and in turn computing the Bayes estimators. We have also derived the Bayes intervals of the parameters and discussed both frequentist and the Bayesian prediction intervals of the future record values based on the observed record values. Monte Carlo simulations are performed to compare the performances of the proposed methods, and one data set has been analyzed for illustrative purposes.

In this article, we generalize the gamma mixed Rayleigh distribution using the quadratic rank transmutation map studied by Shaw et al. [38] to develop a transmuted gamma mixed Rayleigh (TGMR) distribution. We provide a comprehensive description of the mathematical and statistical properties of the subject distribution. We briefly describe different frequentist methods of estimation approaches, namely, maximum likelihood estimators, moments estimators, percentile based estimators, least squares estimators, method of maximum product of spacings, method of Cramér-von-Mises, methods of Anderson-Darling and right-tail Anderson-Darling. Finally, a real data analysis is carried out to illustrate the superiority of the proposed distribution.

This paper is concerned with frequency domain analysis of Markov mean-switching autoregressive (MMSAR) models, linear Markov switching autoregressive (LMSAR) model and transitional Markov switching autoregressive (TMSAR) model. We derive the general

This paper presents a new ordinary least squares model averaging method which is proposed to be a preferable alternative to Mallows Model Averaging (MMA), Bayesian Model Averaging (BMA) and naïve simple forecast average. The method is developed to de

In this paper, we considered a two-stage group acceptance sampling plan based on life tests where the lifetime follows half logistic distribution. The decision on acceptance of lot can be made in the first or second stage according to the number of failures from each group. The design parameters o f the proposed plan such as number of groups required and the acceptance number for each of two stages are determined so as to satisfy the consumer's risk at the specified unreliability when group size and test duration are specified. Single-stage group sampling plans are also considered as special cases of the proposed plan and compared with the proposed plan in terms of the average sample number and the operating characteristics. The results are explained with examples.

The runs test is a well-known test that is used for checking independence between elements of a sample data sequence. Some of runs tests are based on the longest run and others based on the total runs. In this paper, we consider order statistics of two runs statistics, and obtain their probability mass functions. In addition, the means and variances of the order statistics are derived using traditional conditional expectation.

We obtained and investigated consistent, unbiased and efficient estimators of the parameters of irregular right-angled triangular distribution on the basis of maximum likelihood estimators. Some computation results realized on the basis of simulation of the appropriate random samples demonstrate th eoretical outcomes.

We considered the problem of choosing optimal hedging ratio taking into account interday and intraday return de- composition. It was shown that the standard hedging approach which uses only close prices (i.e. daily returns) is inefficient in comparison with hedging strategy based on open and close prices, i.e. when differentiating hedging ratio for interday and intra- day periods. Results are confirmed both by applying Moving Window Regression and Error Correction Model for major world indexes for 1992-2012.