This paper focuses on the application of Markov Chain Monte Carlo (MCMC) technique for estimating the parameters of log-logistic (LL) distribution which is dependent on a complete sample. To find Bayesian estimates for the parameters of the LL model OpenBUGS-established software for Bayesian analysis based on MCMC technique, is employed. It is presumed that samples for independent non informati...

The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic (GL) distribution are introduced. We explore and extend class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantile estimator namely the weighted kernel quantile (WKQ) estimator is proposed to estimate the quantile function. A comparison of these...

We introduce a stochastic process that describes a finite-velocity damped motion on the real line. Differently from the telegraph process, the random times between consecutive velocity changes have exponential distribution with linearly increasing parameters. We obtain the probability law of the motion, which admits a logistic stationary limit in a special case. Various results on the distribut...