Significance of the inclined magnetic field on the water-based hybrid nanofluid flow over a nonlinear stretching sheet.

This work addresses a theoretical exploration of the water-based hybrid nanofluid flow over a nonlinear elongating surface. The flow is taken under the effects of Brownian motion and thermophoresis factors. Additionally, the inclined magnetic field is imposed in the present study to investigate the flow behavior at different angle of inclination. Homotopy analysis approach is used for the solution of modeled equations. Various physical factors, which are encountered during process of transformation, have been discussed physically. It is found that the magnetic factor and angle of inclination have reducing impacts on the velocity profiles of the nanofluid and hybrid nanofluid. The nonlinear index factor has direction relation with the velocity and temperature of the nanofluid and hybrid nanofluid flows. The thermal profiles of the nanofluid and hybrid nanofluid are augmented with the increasing thermophoretic and Brownian motion factors.CuO-H2Onanofluid flow has enhanced heat transfer rate thanAg-H2Onanofluid flow. On the other hand, theCuO-Ag/H2Ohybrid nanofluid has better thermal flow rate thanCuO-H2OandAg-H2Onanofluids. From this table it has noticed that, Nusselt number has increased by 4% for silver nanoparticles whereas for hybrid nanofluid this incrimination is about 15%, which depicts that Nusselt number is higher for hybrid nanoparticles.

Poisson XLindley Distribution for Count Data: Statistical and Reliability Properties with Estimation Techniques and Inference.

In this study, a new one-parameter count distribution is proposed by combining Poisson and XLindley distributions. Some of its statistical and reliability properties including order statistics, hazard rate function, reversed hazard rate function, mode, factorial moments, probability generating function, moment generating function, index of dispersion, Shannon entropy, Mills ratio, mean residual life function, and associated measures are investigated. All these properties can be expressed in explicit forms. It is found that the new probability mass function can be utilized to model positively skewed data with leptokurtic shape. Moreover, the new discrete distribution is considered a proper tool to model equi- and over-dispersed phenomena with increasing hazard rate function. The distribution parameter is estimated by different six estimation approaches, and the behavior of these methods is explored using the Monte Carlo simulation. Finally, two applications to real life are presented herein to illustrate the flexibility of the new model.

A simulation study: Using dual ancillary variable to estimate population mean under stratified random sampling.

In this paper, we propose an improved ratio-in-regression type estimator for the finite population mean under stratified random sampling, by using the ancillary varaible as well as rank of the ancillary varaible. Expressions of the bias and mean square error of the estimators are derived up to the first order of approximation. The present work focused on proper use of the ancillary variable, and it was discussed how ancillary variable can improve the precision of the estimates. Two real data sets as well as simulation study are carried out to observe the performances of the estimators. We demonstrate theoretically and numerically that proposed estimator performs well as compared to all existing estimators.

E-Bayesian and Bayesian Estimation for the Lomax Distribution under Weighted Composite LINEX Loss Function.

The main contribution of this work is the development of a compound LINEX loss function (CLLF) to estimate the shape parameter of the Lomax distribution (LD). The weights are merged into the CLLF to generate a new loss function called the weighted compound LINEX loss function (WCLLF). Then, the WCLLF is used to estimate the LD shape parameter through Bayesian and expected Bayesian (E-Bayesian) estimation. Subsequently, we discuss six different types of loss functions, including square error loss function (SELF), LINEX loss function (LLF), asymmetric loss function (ASLF), entropy loss function (ENLF), CLLF, and WCLLF. In addition, in order to check the performance of the proposed loss function, the Bayesian estimator of WCLLF and the E-Bayesian estimator of WCLLF are used, by performing Monte Carlo simulations. The Bayesian and expected Bayesian by using the proposed loss function is compared with other methods, including maximum likelihood estimation (MLE) and Bayesian and E-Bayesian estimators under different loss functions. The simulation results show that the Bayes estimator according to WCLLF and the E-Bayesian estimator according to WCLLF proposed in this work have the best performance in estimating the shape parameters based on the least mean averaged squared error.