Film Studies in Post-War Poland: Tradition and Innovation

This paper sets out a case for identifying a Carpathian Sprachbund comprising Czech, Slovak, Slovene, Kajkavian Croatian, Hungarian, Yiddish and the Bavarian-Austrian dialect of German. It investigates the distribution of eleven possible Sprachbund-forming features: five phonological (absence of tones, initial stress, phonemic opposition of length in vowels, absence of a palatalization correlation, the presence of medial l), six morpho-syntactical (a basic three-tense verbal system, an analytical future formed with an inchoative plus the infinitive, an original perfect as the only simple preterite, a pluperfect formed from a double perfect, a pre-posed definite and indefinite article). The information gathered comfortably satisfies the minimal conditions for establishing the existence of a Sprachbund set out by Sarah Grey Thomason, W.P. Schmid and others. The levels of participation of the individual languages also seem to be commensurable with those of the languages of the well known Balkan Sprachbund as set forth by Jouko Lindstedt.     

The hidden curriculum of youth care interventions—A case study

Themes such as “effectiveness” and “evidence-based practice” currently dominate debates about the professional care of children and youth. Notwithstanding the importance of these themes, this rather narrow focus may leave the values and ideals underlying youth care interventions undiscussed. In this article we will present our case study of EQUIP as an example of the role of this “hidden curriculum” in youth care interventions. Qualitative research has been conducted, consisting of content analysis of documents, interviews and observations. For the analysis an existing theory on the content and structure of values is used (Schwartz, 1992). The results show that there are distinct differences in the way moral behavior is defined in a Dutch and American “version” of EQUIP. The results also suggest that a difference in value perspective might be related to the effectiveness of the program.     

Simulation-Based Confidence Intervals for Functions With Complicated Derivatives

In many scientific problems, the quantity of interest is a function of parameters that index the model, and confidence intervals are constructed by applying the delta method. However, when the function of interest has complicated derivatives, this standard approach is unattractive and alternative algorithms are required. This article discusses a simple simulation-based algorithm for estimating the variance of a transformation, and demonstrates its simplicity and accuracy by applying it to several statistical problems.     

On robust Bayesian estimation under some asymmetric and bounded loss function

The problem of Bayesian and robust Bayesian estimation with some bounded and asymmetric loss function ABL is considered for various models. The prior distribution is not exactly specified and covers the conjugate family of prior distributions. The posterior regret, most robust and conditional Γ-minimax estimators are constructed and a preliminary comparison with square-error loss and LINEX loss is presented.     

A Euclidean Likelihood Estimator for Bivariate Tail Dependence

The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain moment condition. We propose a Euclidean likelihood-based estimator for the spectral measure which is simple and explicitly defined, with its expression being free of Lagrange multipliers. Our estimator is shown to have the same limit distribution as the maximum empirical likelihood estimator of Einmahl and Segers (2009 Einmahl , J. H. J. , Segers , J. ( 2009 ). Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribution . Ann. Statist. 37 ( 5B ): 2953 – 2989 .[Crossref], [Web of Science ®] , [Google Scholar]). Numerical experiments suggest an overall good performance and identical behavior to the maximum empirical likelihood estimator. We illustrate the method in an extreme temperature data analysis.     

On Prediction for Correlated Domains in Longitudinal Surveys

In the survey sampling estimation or prediction of both population’s and subopulation’s (domain’s) characteristics is one of the key issues. In the case of the estimation or prediction of domain’s characteristics one of the problems is looking for additional sources of information that can be used to increase the accuracy of estimators or predictors. One of these sources may be spatial and temporal autocorrelation. Due to the mean squared error (MSE) estimation, the standard assumption is that random variables are independent for population elements from different domains. If the assumption is taken into account, spatial correlation may be assumed only inside domains. In the paper, we assume some special case of the linear mixed model with two random components that obey assumptions of the first-order spatial autoregressive model SAR(1) (but inside groups of domains instead of domains) and first-order temporal autoregressive model AR(1). Based on the model, the empirical best linear unbiased predictor will be proposed together with an estimator of its MSE taking the spatial correlation between domains into account.     

On the Prediction of the Subpopulation Total Based on Spatially Correlated Longitudinal Data

In a special case of the general linear mixed model, one random component obeys a spatial autoregressive process and another a temporal autoregressive process. The population and any affiliations to subpopulations may change in time. The empirical best linear unbiased predictor is derived and may be used even if the sample size in the subpopulation is null in the period of interest. The mean squared error and its estimator are expressed. The accuracy of the predictor and the bias of the mean squared error estimator are addressed through simulations.