A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

Estimation of the parameter of a dynamically selected population for two subclasses of the exponential family

We introduce the problem of estimation of the parameters of a dynamically selected population in an infinite sequence of random variables and provide its application in the statistical inference based on record values from a non stationary scheme. We develop unbiased estimation of the parameters of the dynamically selected population and evaluate the risk of the estimators. We provide comparisons with natural estimators and obtain asymptotic results. Finally, we illustrate the applicability of the results using real data.     

A version of the Kolmogrov–Feller weak law of large numbers for maximal weighted sums of random variables

Abstract

In this paper we establish Kolmogrov–Feller weak law of large numbers for maximal weighted sums of i.i.d. random variables.     

Supply chain configuration for diffusion of new products: An integrated optimization approach

We develop an integrated/hybrid optimization model for configuring new products’ supply chains while explicitly considering the impact of demand dynamics during new products’ diffusion. The hybrid model simultaneously determines optimal production/sales plan and supply chain configuration. The production and sales plan provides decisions on the optimal timing to launch a new product, as well as the production and sales quantity in each planning period. The supply chain configuration provides optimal selection of options and safety stock level kept at each supply chain function. Extensive computational experiments on randomly generated testbed problems indicate that the hybrid modeling and solution approach significantly outperforms non-hybrid alternative modeling and solution approaches under various diffusion and supply chain topologies. We provide insights on optimal production/sales plan and supply chain configuration for new products during their diffusion process. Also, managerial implications relevant to effectiveness of the hybrid approach are discussed.     

First-session competency: the brief strategic therapy scale-1

The first session in brief strategic therapy is the most critical phase of treatment. More than a mere "assessment phase," the first session in a true intervention sets the stage for all subsequent therapeutic maneuvers. This article presents a supervisory observation tool, the Brief Strategic Therapy Scale-1 (BSTS-1), a fidelity measure proposed as a more formal method of analyzing performance and competency of the therapist for the first session. During scale development, a narrow group of expert judges defined the core skills of therapists and determined the structure/phases of a brief strategic therapy first session. In addition, expert collaborators gave feedback on the scale's usability. This article concludes with the BSTS-1.     

Does Cultural Difference Affect Investment–Cash Flow Sensitivity? Evidence from OECD Countries

We investigate the influence of national culture on corporate investment–cash flow sensitivity. We conjecture that national culture shapes managerial perceptions of information asymmetry and agency problems, thus impacting the investment–cash flow relationship. We document empirical evidence in support of our claim. By linking the investment–cash flow sensitivity to cultural differences, our findings show that, while collectivism has an attenuating influence, uncertainty avoidance, power distance and masculinity have a reinforcing effect on the relationship between cash flow and investment. Our results hold for a sample of 205,268 firm‐years across 24 OECD countries between 1990 and 2017, and are robust after accounting for alternative statistical approaches, sample compositions and measures of cultural dimensions, along with controls for institutional and governmental factors. In addition, by decomposing cash flow into uses and sources of funds in a dynamic multi‐equation model, where firms make financing and investment decisions jointly subject to the constraint that sources must equal uses of cash, we find that national culture shapes how firms react to changes in cash flow.     

On a new positive dependence concept based on the conditional mean inactivity time order

In this paper, we introduce a new positive dependence concept between two non negative random variables which is related to a conditional version of the mean inactivity time order. A number of properties and relationship between the new notion and the concept of positive likelihood ratio dependence (PLRD) is discussed. Some results in terms of proposed notions for the Archimedean family of copulas are provided.     

Bayesian prediction of minimal repair times of a series system based on hybrid censored sample of components’ lifetimes under Rayleigh distribution

In this paper, we develop Bayesian predictive inferential procedures for prediction of repair times of a series system, applying a minimal repair strategy, using the information contained in an independent observed hybrid censored sample of the lifetimes of the components of the system, assuming the underlying distribution of the lifetimes to be Rayleigh distribution. An illustrative real data example and a simulation study are presented for the purpose of illustration and comparison of the proposed predictors.     

Simulation Modeling and Analysis: A Collateral Application and Exposition of RFID Technology

RFID technology provides in‐depth, real‐time visibility into the status of assets throughout the supply chain. However, the deployment of RFID technology may have collateral value in the high‐quality data generated by these assets. This study explores the potential value of RFID data for tactical and strategic purposes and the redesign of processes within supply chain through the deployment of simulation modeling and analysis. We present a simulation study conducted at a regional hospital for which data related to trauma patient movement was collected with an RFID‐based system. We find that not only does this data serve as the basis for successful simulation modeling, but that RFID technology may address several data‐related challenges previously identified in the simulation literature.