Multitude of Laplace distributions

Motivated by the recent popularity, we provide a comprehensive review of the known Laplace distributions along with their properties and applications.     

The power of the intelligentsia: The Rywin Affair and the challenge of applying the concept of cultural capital to analyze Poland’s elites

This article aims at integrating the phenomenon of the Central and Eastern European intelligentsia into the application of the theory of cultural capital of Pierre Bourdieu to the analysis of societies of that region. This is done by critically reevaluating the model of evolution of the post-communist countries of Central Europe proposed by Gil Eyal, Ivan Szelényi, and Eleanor Townsley, in their “Making Capitalism without Capitalists.” The present article argues for supplementing their approach with an analytical distinction between the concepts of intellectuals (as masters of the critical discourse culture) and the intelligentsia, which in countries like Poland have an important component of post-gentry culture. The identity and images of the intelligentsia are analyzed as important though highly contested aspects of cultural capital in Poland. Wide implications of discursive battles on the status of intelligentsia in contemporary Poland are exemplified in the case of the debates over the so-called Rywin Affair in Poland and the role played in that affair by the major Polish intellectual Adam Michnik. The political discourse related to the affair and to the status of Michnik are studied in context of the structure of the Polish political scene and related to the academic debates on the intelligentsia, whether it is a “really existing” and significant social group or merely a marginal one and “outdated discourse.”     

Imagining is Not Observing: The Role of Simulation Processes Within the Mimicry-Liking Expressway

Journal of Nonverbal Behavior - Individuals automatically mimic a wide range of different behaviors, and such mimicking behavior has several social benefits. One of the landmark findings in the...     

On prediction of population and subpopulation characteristics for future periods

The estimation or prediction of population characteristics based on the sample information is the key issue in survey sampling. If the sample sizes in subpopulations (domains) are large enough, similar methods as used for the whole population can be used to estimate or to predict subpopulations characteristics as well. To estimate or to predict characteristics of domains with small or even zero sample sizes, small area estimation methods “borrowing strength” from other subpopulations or time periods are widely used. We extend this problem and study methods of prediction of future population and subpopulations’ characteristics based on the longitudinal data.     

Evaluation of Laplace distribution-based ANOVA models applied to microarray data

In a microarray experiment, intensity measurements tend to vary due to various systematic and random effects, which enter at the different stages of the measurement process. Common test statistics do not take these effects into account. An alternative is to use, for example, ANOVA models. In many cases, we can, however, not make the assumption of normally distributed error terms. Purdom and Holmes [6 Purdom, E. and Holmes, S. P. 2005. Error distribution for gene expression data. Stat. Appl. Genet. Mol. Biol., 4(1) article 16 [Google Scholar]] have concluded that the distribution of microarray intensity measurements can often be better approximated by a Laplace distribution. In this paper, we consider the analysis of microarray data by using ANOVA models under the assumption of Laplace-distributed error terms. We explain the methodology and discuss problems related to fitting of this type of models. In addition to evaluating the models using several real-life microarray experiments, we conduct a simulation study to investigate different aspects of the models in detail. We find that, while the normal model is less sensitive to model misspecifications, the Laplace model has more power when the data are truly Laplace distributed. However, in the latter situation, neither of the models is able to control the false discovery rate at the pre-specified significance level. This problem is most likely related to sample size issues.     

Stochastic Choice and Revealed Perturbed Utility

Perturbed utility functions—the sum of expected utility and a nonlinear perturbation function—provide a simple and tractable way to model various sorts of stochastic choice. We provide two easily understood conditions each of which characterizes this representation: One condition generalizes the acyclicity condition used in revealed preference theory, and the other generalizes Luce's IIA condition. We relate the discrimination or selectivity of choice rules to properties of their associated perturbations, both across different agents and across decision problems. We also show that these representations correspond to a form of ambiguity‐averse preferences for an agent who is uncertain about her true utility.     

ON PREDICTION OF TOTAL VALUE IN INCOMPLETELY SPECIFIED DOMAINS

This paper presents the problem of prediction of a domain total value based on the general linear model. In many methods presented in the survey sampling literature (e.g. Cassel, Särndal & Wretman, 1977 [Foundations of inference in survey sampling, New York: John Wiley & Sons]; Valliant, Dorfman & Royall, 2000 [Finite population sampling and inference. A prediction approach. New York: John Wiley & Sons]; Rao, 2003 [Small area estimation. New York; John Wiley & Sons]) a common assumption is that for each element of a population the domain to which it belongs is known. This assumption is especially important in the situation when a superpopulation model with auxiliary variables is considered. In this paper a method is proposed for prediction of the domain total when it is not known whether a unit belongs to a given domain or not, or when the information is available only for sampled elements of the population.     

Sharp bounds on l-estimates and their expectations for dependent samples

Sharp bounds on the expectation of each L-estimate are determined for samples of identically distributed random variables with a given expectation and a central absolute moment of order p > 1, The distributions achieving these bounds are constructed. Analogous results are derived in the cases of symmetric, noraiegative and bounded random variables, Accurate bounds for L-estimates of arbitrary finite samples are concluded.