Television and Violence in the Economy of Memory

The present paper aims to consider the cultural function of television as a technology for the creation of a public memory. The television system records past images, preserves them, and broadcasts various historical programs. A viewer owns the public memory jointly, through watching/consuming programs. However, the process of production and consumption of programs is linked with the exclusion of other historical memories from the public space. After all, the creation of public memories in depth is related to social power. Through the analysis in concrete terms of a series of programs of Project X and the second episode of the Nippon Hoso Kyokai (NHK; Japan Broadcasting Corporation) series, Special Edition: Judging War, the relationship between the organization of public memories and social power is explored. Project X depicts the challenges of engineers of middle standing who initiated new industrial and technological developments in the 1960s and 1970s. Special Edition: Judging War is based on coverage of the Women's International War Crimes Tribunal on Japan's Military Sexual Slavery. This program was subjected to revision on the eve of its broadcast. What forms of expression were eliminated? These two programs should help us define more clearly what the Japanese media selects for incorporation into the public memory.     

A multivariate zero-inflated binomial model for the analysis of correlated proportional data

In this paper, a new multivariate zero-inflated binomial (MZIB) distribution is proposed to analyse the correlated proportional data with excessive zeros. The distributional properties of purposed model are studied. The Fisher scoring algorithm and EM algorithm are given for the computation of estimates of parameters in the proposed MZIB model with/without covariates. The score tests and the likelihood ratio tests are derived for assessing both the zero-inflation and the equality of multiple binomial probabilities in correlated proportional data. A limited simulation study is performed to evaluate the performance of derived EM algorithms for the estimation of parameters in the model with/without covariates and to compare the nominal levels and powers of both score tests and likelihood ratio tests. The whitefly data is used to illustrate the proposed methodologies.     

从认知视角分析英、法、汉语的通感现象

通感不能简单地理解为语言系统中的词义特征,它不仅是一种修辞手段,一种生理或者心理现象,而与隐喻一样是人类认知世界的一种方式。本文从视、听、嗅、味、触五大感官分类对英、法、汉三语中若干相互对应的词汇和短句通感现象进行了分析,以证明通感是人类普遍的认知方式,并在分析对比中进一步深化了对语言通感现象的研究。     

Strong previsions of random elements

LetC be a class of arbitrary real random elements andP an extended real valued function onC. Two definitions of coherence forP are compared. Both definitions reduce to the classical de Finetti's one whenC includes bounded random elements only. One of the two definitions (called strong coherence) is investigated, and some criteria for checking it are provided. Moreover, conditions are given for the integral representation of a coherentP, possibly with respect to a δ-additive probability. Finally, the two definitions and the integral representation theorems are extended to the case whereC is a class of random elements taking values in a given Banach space.     

Non-parametric Estimation of the Residual Distribution

Consider a heteroscedastic regression model Y = m ( X ) +σ( X )ε, where the functions m and σ are smooth, and ε is independent of X . An estimator of the distribution of ε based on non-parametric regression residuals is proposed and its weak convergence is obtained. Applications to prediction intervals and goodness-of-fit tests are discussed.     

Generation of multivariate distributions by vertical density representation

Troutt (1991,1993) proposed the idea of the vertical density representation (VDR) based on Box-Millar method. Kotz, Fang and Liang (1997) provided a systematic study on the multivariate vertical density representation (MVDR). Suppose that we want to generate a random vector X[d]Rⁿthat has a density function ?(x). The key point of using the MVDR is to generate the uniform distribution on [D]_?(v) = {x :?(x) = v} for any v > 0 which is the surface in RⁿIn this paper we use the conditional distribution method to generate the uniform distribution on a domain or on some surface and based on it we proposed an alternative version of the MVDR(type 2 MVDR), by which one can transfer the problem of generating a random vector X with given density f to one of generating (X, X_n+i) that follows the uniform distribution on a region in Rⁿ⁺¹defined by ?. Several examples indicate that the proposed method is quite practical.     

A class of weighted normal distributions and its variants useful for inequality constrained analysis

This article develops a class of the weighted normal distributions for which the probability density function has the form of a product of a normal density and a weight function. The class constitutes marginal distributions obtained from various kinds of doubly truncated bivariate normal distributions. This class of distributions strictly includes the normal, skew–normal and two-piece skew–normal and is useful for selection modelling and inequality constrained normal mean analysis. Some distributional properties and Bayesian perspectives of the class are given. Probabilistic representation of the distributions is also given. The representation is shown to be straightforward to specify distribution and to implement computation, with output readily adapted for required analysis. Necessary theories and illustrative examples are provided.     

Discrete Multicolour Random Mosaics with an Application to Network Extraction

We introduce a class of random fields that can be understood as discrete versions of multicolour polygonal fields built on regular linear tessellations. We focus first on a subclass of consistent polygonal fields, for which we show Markovianity and solvability by means of a dynamic representation. This representation is used to design new sampling techniques for Gibbsian modifications of such fields, a class which covers lattice‐based random fields. A flux‐based modification is applied to the extraction of the field tracks network from a Synthetic Aperture Radar image of a rural area.     

A Class of Multivariate Bilateral Selection t Distributions and Its Properties

This article proposes a class of multivariate bilateral selection t distributions useful for analyzing non-normal (skewed and/or bimodal) multivariate data. The class is associated with a bilateral selection mechanism, and it is obtained from a marginal distribution of the centrally truncated multivariate t. It is flexible enough to include the multivariate t and multivariate skew-t distributions and mathematically tractable enough to account for central truncation of a hidden t variable. The class, closed under linear transformation, marginal, and conditional operations, is studied from several aspects such as shape of the probability density function, conditioning of a distribution, scale mixtures of multivariate normal, and a probabilistic representation. The relationships among these aspects are given, and various properties of the class are also discussed. Necessary theories and two applications are provided.