In this paper we have proposed a new family of distributions; the Topp-Leone family of distributions. We have given general expression for density and distribution function of the new family. Expression for moments and hazard rate has also been given. We have also given an example of the proposed family.

No abstract

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 informative set of priors for estimating LL parameters are drawn from posterior density function. A proposed module was developed and incorporated in OpenBUGS to estimate the Bayes estimators of the LL distribution. It is shown that statistically consistent parameter estimates and their respective credible intervals can be constructed through the use of OpenBUGS. Finally comparison of maximum likelihood estimate and Bayes estimates is carried out using three plots. Additively through this research it is established that computationally MCMC technique can be effortlessly put into practice. Elaborate procedure for applying MCMC, to estimate parameters of LL model, is demonstrated by making use of real survival data relating to bladder cancer patients.

The simple circuit based on DC-DC converters is the main attractive feature of the differential inverter topologies. It has a single-stage and provides modularity and scalability. However, the Negative Sequence Harmonic Component (NSHC) generated at the output terminal may hinder its practical applications. This paper presents a single-stage three-phase isolated differential inverter based on three High-Frequency Link (HFL) transformer-based DC-DC SEPIC converters. The utilized SEPIC converters perform voltage step-up/ down capability with galvanic isolation, which is essential for Renewable Energy Sources (RES). It mitigates the Common-Mode Voltage (CMV) and ElectroMagnetic Interference (EMI). Moreover, this paper proposes a two-loop based d-q synchronous frame grid-current control to mitigate its NSHC. A Type-II compensator and simple NSHC detection circuit are proposed to enhance the inverter's stability and compensate phase-delay of the utilized SEPIC converters. NSHC detection is developed using three cascaded Low Path Filters (LPFs). A 1.6kW inverter prototype was set to validate the performance of the proposed inverter and its control. The control is implemented by the MWPE3 C6713A Expert III DSP board. The proposed topology has a maximum efficiency of 89.744 at 700W output power and 86.4% at full power. The proposed control decreases the NSHC from 40.6 % to 1.614%, which shows its accuracy and precision. Furthermore, THD is reduced from 35.61% to 4.087% and satisfy the recent grid codes (<5%). The simulation results using PSIM software, power loss distribution, and a comparison study of the proposed inverter with similar topologies are also presented.