Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

The neglected mediating role of self-efficacy in the goal setting process in local public administrations

To analyse the role of self-efficacy in goal setting in public administrations, this study combines goal-setting theory, public service motivation literature and cognitive theory. Using partial least squares structural equation modelling (PLS-SEM), survey data from 105 German civil servants are analysed. The results underline the role of goal setting (represented by goal difficulty and specificity) in determining the self-efficacy of public servants. Public service motivation and goal specificity both increase public servants’ work performance; however, the effects of goal difficulty are negatively mediated by the employee’s self-efficacy. That finding reflects the central role of self-efficacy, which should not be ignored in the goal-setting processes of public administrations.     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Exploring in Silence: Hearing and Deaf Infants Explore Objects Differently Before Cochlear Implantation

Infant development has rarely been informed by the behavior of infants with sensory differences despite increasing recognition that infant behavior itself creates sensory learning opportunities. The purpose of this study of object exploration was to compare the behavior of hearing and deaf infants, with and without cochlear implants, in order to identify the effects of profound sensorineural hearing loss on infant exploration before cochlear implantation, the behavioral effects of access to auditory feedback after cochlear implantation, and the sensory motivation for exploration behaviors performed by hearing infants as well. The results showed that 9‐month‐old deaf infants explored objects as often as hearing infants but they used systematically different approaches and less variation before compared to after cochlear implantation. Potential associations between these early experiences and later learning are discussed in the context of embodied developmental theory, comparative studies, and research with adults. The data call for increased recognition of the active sensorimotor nature of infant learning and future research that investigates differences in sensorimotor experience as potential mechanisms in later learning and sequential memory development.     

Developing a Rubric for Supervision of Students Counseling LGBTQ Clients

More than 100 pieces of anti-lesbian, gay, bisexual, transgender (LGBT) legislation are active in 2018. In this current political climate of “conscience clause” legislation, counselor educators and supervisors are poised to adopt more holistic practices in assessing and evaluating student and supervisee readiness to work with LGBT queer (Q) clients. The purpose of this article is to present a dispositional framework for assessment and evaluation and introduce the flexibility, integrity, awareness, stability, compassion, and openness (FIASCO) rubric of professional counseling dispositions. Two court cases, Keeton v. Anderson-Wiley and Ward v. Wilbanks, are used as case examples for applying the FIASCO rubric to situations involving LGBTQ clients.