Sri Astuti Thamrin

On some examples of pollutant transport problems solved numerically using the boundary element method

A boundary element method (BEM) is obtained for solving a boundary value problem of homogeneous anisotropic media governed by diffusion-convection equation. The application of the BEM is shown for two particular pollutant transport problems of Tello river and Unhas lake in Makassar Indonesia. For the two particular problems a variety of the coefficients of diffusion and the velocity components are taken. The results show that the solutions vary as the parameters change. And this suggests that one has to be careful in measuring or determining the values of the parameters.

Bayesian inference for spatial parametric proportional hazards model using Spatsurv R

In many fields of applied studies, there has been increasing interest in developing and implementing Bayesian statistical methods for modelling and analysing the time-to-event data. Modelling the time-to-event data can be done by using the survival methods. In the survival data, we can find a set of complete records, in which the event and the survival time is known; and a set of censored records, in which the event was known to have occurred in an interval, but the survival time is unknown exactly. The time of an event frequently depends on the location; calls as spatial survival. In this paper, we performed a simulation study to estimate the spatial survival model parameters. The study was carried out with two different simulated datasets with right censored, which is, simulated assuming an exponential baseline hazard and a Weibull baseline hazard. The parametric proportional hazards model in which spatially correlated frailties with a log-Gaussian is the specific type of spatial model which is used. Th...

Estimating piecewise exponential frailty model with changing prior for baseline hazard function

Piecewise exponential models provide a very flexible framework for modelling univariate survival data. It can be used to estimate the effects of different covariates which are influenced by the survival data. Although in a strict sense it is a parametric model, a piecewise exponential hazard can approximate any shape of a parametric baseline hazard. In the parametric baseline hazard, the hazard function for each individual may depend on a set of risk factors or explanatory variables. However, it usually does not explain all such variables which are known or measurable, and these variables become interesting to be considered. This unknown and unobservable risk factor of the hazard function is often termed as the individual’s heterogeneity or frailty. This paper analyses the effects of unobserved population heterogeneity in patients’ survival times. The issue of model choice through variable selection is also considered. A sensitivity analysis is conducted to assess the influence of the prior for each param...