Research ArticleOpen accessIn the author namesGAUSSIAN COPULA MARGINAL REGRESSION FOR MODELING EXTREME DATA WITH APPLICATIONSutikno, Heri Kuswanto, Iis Dewi RatihRegression is commonly used to determine the relationship between the response variable and the predictor variable, where the parameters are estimated by Ordinary Least Square (OLS). This method can be used with an assumption that residuals are normally distributed (0, σ2). However, the assumption of normality of the data is often violated due to extreme observations, which are often found … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 4 Apr 2014 · 7,620 accessesView PDFCite
Research ArticleOpen accessIn the author namesMAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODELRokhana Dwi Bekti, Anita Rahayu, SutiknoSpatial Durbin Model (SDM) is one method of spatial autoregressive. This model was developed because the dependencies in the spatial relationships not only occur in the dependent variable, but also on the independent variables. In the assessment of parameter estimation, the process is carried out by Maximum Likelihood Estimation (MLE). This estimation can be approximation by Spatial Autoregressive Models (SAR). … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 15 Jun 2013 · 8,636 accessesView PDFCite
Research ArticleOpen accessIn the author namesSpatial Durbin Model to Identify Influential Factors of DiarrheaRokhana Dwi Bekti, SutiknoProblem statement: An analysis of regression modeling which influenced by the characteristics of the region is very important. That modeling is the spatial autoregressive model. One type of spatial autoregressive model is a Spatial Durbin Model (SDM), which performs a lag effect of the dependent and independent variables. This model was developed because the dependencies in the spatial relationships doesn’t … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 8,282 accessesView PDFCite
Research ArticleOpen accessIn the author namesThe Development of Parameter Estimation on Hazard Rate of Trivariate Weibull DistributionIrfan Wahyudi, Purhadi, Irhamah, SutiknoIn this study, the interrelation concepts of trivariate distribution function, trivariate survival function, trivariate probability density function and trivariate hazard rate function of trivariate Weibull distribution are presented. The goal of this contribution is to estimate the trivariate Weibull hazard rate parameters. To reach this goal, we will use an analitical approach in estimating called the Maximum Likelihood Estimation (MLE) … …Current Research in Biostatistics, Vol. 2, Issue 2 · 11 Aug 2012 · 8,923 accessesView PDFCite