Model Assisted Statistics and Applications - Volume 13, issue 2

Authors: Thamanukornsri, Chompunooch | Tiensuwan, Montip

Article Type: Research Article

Abstract: In this paper, we focus on monthly number of dengue cases in Thailand using the univariate Box-Jenkins (seasonal ARIMA) and GARCH models. There are 3 types of dengue i.e. dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). These series are fitted with adjustment by population size and seasonal index. For each type, the best model is choosen by Akaike’s Information Criteria (AIC) and Schwartz’s Bayesian Criteria (SBC). A comparison of the fitted Box-Jenkins and GARCH models are presented using root mean square error (RMSE) and mean absolute percentage error (MAPE). The results showed that the best …fitted for the univariate Box-Jenkins models of DF, DHF and DSS cases are seasonal ARIMA(0, 1, 1) × (0, 1, 1) 12 , ARIMA(0, 1, 1) × (0, 1, 1) 12 and ARIMA(0, 1, 3) × (0, 1, 1) 12 , respectively, while the best fitted GARCH models of DF, DHF and DSS cases are AR(1)-GARCH(1, 1) adjusted seasonal components, AR(8)-ARCH(1) removed seasonal components and AR(1)-ARCH(1) adjusted seasonal components, consequently. Further, from a comparison the GARCH model outperforms than the univariate Box-Jenkins (seasonal ARIMA) model. Removing seasonal components technique increased efficiency of fitting model in GARCH method while adjustment by population size did not give a significantly difference result to both methods. Show more

Keywords: Dengue fever, dengue hemorrhagic fever, dengue shock syndrome, population size, seasonal index

DOI: 10.3233/MAS-180422

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 95-105, 2018

Authors: Sen, Subhradev | Chandra, N. | Maiti, Sudhansu S.

Article Type: Research Article

Abstract: In this article, we have investigated some further distributional properties (such as, characteristic and generating functions, distributions of extreme order statistics, important entropy measures) and some additional survival and/or reliability characteristics (such as, time to failure, ageing intensity, stress-strength reliability) of one parameter xgamma distribution which serves as an useful survival model. We also studied the estimation procedures of the model parameter and its important survival characteristics considering maximum likelihood and Bayesian techniques under progressively type-II right censoring scheme. Interval estimation and coverage probability for the parameter were obtained based on maximum likelihood estimation. A Monte-Carlo simulation study was conducted …to compare performance of the various estimates. Progressively type-II censoring scheme was considered in view of cost and time constraints. A real data were also analyzed for illustrating the methods described in the paper. Show more

Keywords: Lifetime distribution, survival analysis, progressive censoring, maximum likelihood, Bayes methodAMS Classification: MSC 62E10, MSC 62N02, MSC 62F15

DOI: 10.3233/MAS-180423

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 107-121, 2018

Authors: Diana, Rita

Article Type: Research Article

Abstract: A multivariable semiparametric regression model is a combination of parametric and nonparametric regressions, the parametric component of which refers to polynomial patterns, while its nonparametric component does not have certain pattern. This nonparametric component can be fitted with smoothing spline function. This reearch is aimed to to develop a multivariable semiparametric regression model through fully Bayesian approach for cross-sectional data. The development is meant to be implemented in analysing Open Unemployment Rate (OUR) in East Java Province, Indonesia. The result applying the model in estimating the Open Unemployment Rate (OUR) in East Java province reveals that multivariable semiparametric regression model …with parametric component, based on macro economy, corresponds to linear and the nonparametric components corresponds to cubic smoothing spline function using fully Bayesian approach. The parametric component includes the percentage of population with higher education and regional minimum wage. The nonparametric component includes economic growth, population density, large-sized and medium-sized industries ratio. In conclusion, the smoothing spline modeling using fully Bayesian approach shows better performance than using Bayesian approach. Show more

Keywords: Fully Bayesian, Gibbs sampling, MCMC, multivariable semiparametric regression, smoothing spline, open unemployment rate

DOI: 10.3233/MAS-180424

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 123-132, 2018

Authors: Osahan, Sukhminder S.

Article Type: Research Article

Abstract: Sub-studies addressing specific research questions may necessitate selecting a random sample from different eligibility groups of The World Trade Center Health Registry (WTCHR) for estimating population parameter mean. In such a situation, Singh (1988) and Osahan (1997) proposed three two-stage sampling strategies in overlapping clusters. These sampling strategies are compared using WTCHR’s overlapping eligibility groups, in terms of their bias and efficiency.

Keywords: Overlapping clusters, two-stage sampling, eligibility groups, probabilities proportional to size, bias, efficiency

DOI: 10.3233/MAS-180425

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 133-140, 2018

Authors: Icuma, Tatiana Reis | Achcar, Jorge Alberto | Martinez, Edson Zangiacomi | Davarzani, Nasser

Article Type: Research Article

Abstract: The estimation of optimum cut points for covariates in lifetime regression models is of great interest under a medical view. Usually the choice of covariate cut points is made in an arbitrary way following the clinical expert knowledge. In this paper, it is proposed a simple and practical Bayesian approach which could be used to different lifetime distributions under AFT (accelerated failure time) modeling approach assuming censored or uncensored data to get optimum cut points with larger prognostic effects. For the Bayesian approach, MCMC simulations are used to get estimation for the cut points under a squared error loss (SEL) …function. The proposed methodology is illustrated with three medical lifetime data sets. Show more

Keywords: Lifetime data, censoring, accelerated failure time models, cut points, Bayesian approach, MCMC methods

DOI: 10.3233/MAS-180426

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 141-159, 2018

Authors: Moiseev, Nikita A. | Sorokin, Aleksander S.

Article Type: Research Article

Abstract: This paper is aimed at the analysis and verification of the formula for computing the number of degrees of freedom for the combined model when averaging across a set of regression models, which was proposed by Moiseev (2017) but was not thoroughly analyzed. The key feature of this formula is that it is applicable to absolutely any averaging method what dramatically widens its scope of application. We notice that the exact number of degrees of freedom for the combined model can not be computed due to uncertainty of variance-covariance matrix of submodels’ errors. However, it is shown by conducted simulation …study that even using unbiased estimator of this matrix yields reliable confidence intervals. Therefore, considered formula appears to be crucial when computing interval forecast by model averaging methods. Show more

Keywords: Interval forecast, confidence intervals, degrees of freedom, t-distribution, forecast combination, model averaging, mean-squared forecast error model averaging JEL codes: C52, C53

DOI: 10.3233/MAS-180427

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 161-172, 2018

Authors: Dubbs, Alexander

Article Type: Research Article

Abstract: We use a simple machine learning model, logistically-weighted regularized linear least squares regression, in order to predict baseball, basketball, football, and hockey games. We do so using only the thirty-year record of which visiting teams played which home teams, on what date, and what the final score was. No real statistics are used, although a statistical method is used. The method works best in basketball, likely because it is high-scoring and has long seasons. It works better in football and hockey than in baseball, but in baseball the predictions are closer to a theoretical optimum. The football predictions, while good, …can in principle be made much better, and the hockey predictions can be made somewhat better. These findings tells us that in basketball, most statistics are subsumed by the scores of the games, whereas in football, further study of game and player statistics is necessary to predict games as well as can be done. Baseball and hockey lie somewhere in between. Show more

Keywords: Sports prediction, ridge regression

DOI: 10.3233/MAS-180428

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 173-181, 2018

Authors: Dronov, Sergei V. | Evdokimov, Eugeny A.

Article Type: Research Article

Abstract: In this paper, one of the variants of so-called post-hoc cluster analysis problem is considered: the characteristics by which the clusters were constructed are ranked according to the degree of their influence on the final cluster partition. Wherein, using the pairwise coefficients proposed in the paper, we estimate the possibility of replacing a pair of characteristics by one of them (the degree of dominance of one characteristic over another), and the strength of the kind of mutual influence of the characteristics that is associated with the existing cluster structure. The latter influence we call a cluster connection. The most meaningful …results were obtained, assuming that the addition or elimination of any forming characteristic leads to the grinding or consolidation of clusters, which is true for the algorithms of hierarchical classification. Show more

Keywords: Cluster connection, forming characteristics, cluster dominance, post-hoc problem in cluster analysis, hierarchical cluster

DOI: 10.3233/MAS-180429

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 183-195, 2018

Authors: Ren, Luh Yu (Louie) | Ren, Christine

Article Type: Research Article

Abstract: The purpose of this study is to examine the Sex Dimorphism Ratio (SDR) for a wide range of age groups in two environments, the suburbs of Los Angeles and Taiwan, which differ in height distribution. Using statistics, we examine if SDR will alter due to the change in woman’s reproductive viability. Two-way Analysis of Variance (ANOVA) in the form of multiple regression analysis with dummy variables and traditional regression analysis are applied. The results show that SDR approximately follows the required normal distribution, there is no interaction between age and environment, and there is no difference in SDRs among the …36 age groups. The only factor that affects the mean of the SDR is the environmental difference. The results imply that SDR remains constant throughout our lifespan despite changes in our personal reproductive viability. The ideal SDR is not fixed because different height probability distributions in different environments may have different optimal SDRs. The minimum SDR stays fairly constant, though statistically different from two different environments in our study. The maximum SDR from one environment in this study is much higher than that from the other. Show more

Keywords: List-wise deletion method, multiple regression analysis with dummy variables, reproductive fitness, Sex Dimorphism Ratio, two-way analysis of variance

DOI: 10.3233/MAS-180430

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 197-204, 2018

Article Type: Research Article

DOI: 10.3233/MAS-180431

Citation: Model Assisted Statistics and Applications, vol. 13, no. 2, pp. 205-, 2018