Quantile based tests for exponentiality against DMRQ and NBUE alternatives

Quantile-based reliability analysis has received much attention recently. We propose new quantile-based tests for exponentiality against decreasing mean residual quantile function (DMRQ) and new better than used in expectation (NBUE) classes of alternatives. The exact null distribution of the test statistic is derived when the alternative class is DMRQ. The asymptotic properties of both the test statistics are studied. The performance of the proposed tests with other existing tests in the literature is evaluated through simulation study. Finally, we illustrate our test procedure using real data sets.     

The Revenge of History – The Institutional Roots of Post‐Communist Family Policy in the Czech Republic,Hungary and Poland

The authors combine historical and sociological institutional analysis to show that despite the political and socio‐economic transformation in 1990s, the institutional development during and before the communist era provides the best explanation for current childcare policies in Central Europe. While most authors have concentrated on policy changes that have taken place in the region since 1989, this article concentrates on the historical roots of these policies and shows that today's policies are highly influenced by a certain dynamics that had already emerged under communist rule. It shows that a historical institutional approach, which analyses the ‘gendered logic of appropriateness’ and policy legacies at various critical junctures, can explain why family policies in Central Europe had already begun to differ during the communist era, why these main differences continue and why even the changes that have taken place follow logically from historical‐institutional developments.     

Coverage Properties of Confidence Intervals for Generalized Additive Model Components

Abstract. We study the coverage properties of Bayesian confidence intervals for the smooth component functions of generalized additive models (GAMs) represented using any penalized regression spline approach. The intervals are the usual generalization of the intervals first proposed by Wahba and Silverman in 1983 and 1985, respectively, to the GAM component context. We present simulation evidence showing these intervals have close to nominal ‘across‐the‐function’ frequentist coverage probabilities, except when the truth is close to a straight line/plane function. We extend the argument introduced by Nychka in 1988 for univariate smoothing splines to explain these results. The theoretical argument suggests that close to nominal coverage probabilities can be achieved, provided that heavy oversmoothing is avoided, so that the bias is not too large a proportion of the sampling variability. The theoretical results allow us to derive alternative intervals from a purely frequentist point of view, and to explain the impact that the neglect of smoothing parameter variability has on confidence interval performance. They also suggest switching the target of inference for component‐wise intervals away from smooth components in the space of the GAM identifiability constraints.     

A consistent parameter estimation in the three-parameter lognormal distribution

In this work, we propose a consistent method of estimation for the parameters of the three-parameter lognormal distribution. We then discuss some properties of these estimators and show by means of a Monte Carlo simulation study that the proposed estimators perform better than some other prominent estimators in terms of bias and root mean squared error. Finally, we present two real-life examples to illustrate the method of estimation proposed.     

Nonparametric estimation of the derivatives of a density by the method of wavelet for mixing sequences

The problem of estimation of the derivative of a probability density f is considered, using wavelet orthogonal bases. We consider an important kind of dependent random variables, the so-called mixing random variables and investigate the precise asymptotic expression for the mean integrated error of the wavelet estimators. We show that the mean integrated error of the proposed estimator attains the same rate as when the observations are independent, under certain week dependence conditions imposed to the {X _i }, defined in {Ω, N, P}.     

Seven useful designs

When designing a clinical trial there is a need to design a study that achieves the objectives of a trial both efficiently and with minimum resources. This paper describes seven trial designs that could possibly be used in clinical development and highlights how a design although not optimal for an individual study may be optimal for a wider clinical program.     

Countervailing institutional forces: corporate governance in Turkish family business groups

This longitudinal study investigates the impact of national and international pressures to improve corporate governance in an emerging economy from an institutional theory perspective. Recently, family business groups (FBGs), the dominant form of organizing in emerging economies, have been criticized by policy makers for their poor governance structures. A common recommendation to FBGs has been increasing the number of independent, outsider directors on their boards. Thus, change in the board compositions of the quoted subsidiaries of the six biggest FBGs is analyzed over 2002–2006. One-way-ANOVA and t-tests were used as statistical tools. Findings reveal that there has not been a statistically significant change in board compositions over the research period. FBGs were found to resist institutional pressures through ‘avoidance’, ‘defiance’ and “manipulation” strategies due to the absence of coercive pressures and multiple forms of ‘institutional work’ for change.     

Extrapolative simulation of neighborhood networks based on population spatial distribution: Do they predict crime?

Objectives

Previous criminological scholarship has posited that network ties among neighborhood residents may impact crime rates, but has done little to consider the specific ways in which network structure may enhance or inhibit criminal activity. A lack of data on social ties has arguably led to this state of affairs. We propose to avoid this limitation by demonstrating a novel approach of extrapolatively simulating network ties and constructing structural network measures to assess their effect on neighborhood crime rates.

Methods

We first spatially locate the households of a city into their constituent blocks. Then, we employ spatial interaction functions based on prior empirical work and simulate a network of social ties among these residents. From this simulated network, we compute network statistics that more appropriately capture the notions of cohesion and information diffusion that underlie theories of networks and crime.

Results

We show that these network statistics are robust predictors of the levels of crime in five separate cities (above standard controls) at the very micro geographic level of blocks and block groups.

Conclusions

We conclude by considering extensions of the approach that account for homophily in the formation of network ties.