the purpose of this work is to promote and facilitate forensic profiling and chemical analysis of illicit drug samples in order to determine their origin, methods of production and transfer through the country. the article is based on the gas chromatography analysis of heroin samples seized from three different locations in serbia. chemometric approach with appropriate statistical tools (multip...

Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...

We address a quantile dependent prior for Bayesian quantile regression. We extend the idea of the power prior distribution in Bayesian quantile regression by employing the likelihood function that is based on a location-scale mixture representation of the asymmetric Laplace distribution. The propriety of the power prior is one of the critical issues in Bayesian analysis. Thus, we discuss the pr...

reduced differental transform method (rdtm), which isone of the useful and effective numerical method, is applied to solve nonlinear time-dependent foam drainage equation (fde) with different initial conditions. we compare our method with the famous adomian decomposition and laplace decomposition methods. the obtained resultsdemonstrated that rdtm is a powerful tool for solving nonlinear par...

Using an asymmetric Laplace distribution, which provides a mechanism for Bayesian inference of quantile regression models, we develop a fully Bayesian approach to fitting single-index models in conditional quantile regression. In this work, we use a Gaussian process prior for the unknown nonparametric link function and a Laplace distribution on the index vector, with the latter motivated by the...

We consider an inference method for prediction based on belief functions in quantile regression with an asymmetric Laplace distribution. Specifically, we apply this method to the capital asset pricing model to estimate the beta coefficient and measure volatility under various market conditions at given levels of quantile. Likelihood-based belief functions are calculated from historical data of ...

aim : in this study, we aimed to estimate one- to five-year survival rates in iranian patients with gastric cancer (gc). in addition, we preformed subgroup analyses and meta-regression to explore possible sources of heterogeneity between studies.   background : according to literatures, there has been increasing attention to the long-term survival rate in patients with gc in iran. however, resu...