Variable selection for first‐order Poisson integer‐valued autoregressive model with covariables

In recent years, modelling count data has become one of the most important and popular topics in time‐series analysis. At the same time, variable selection methods have become widely used in many fields as an effective statistical modelling tool. In this paper, we consider using a variable selection method to solve a modelling problem regarding the first‐order Poisson integer‐valued autoregressive (PINAR(1)) model with covariables. The PINAR(1) model with covariables is widely used in many areas because of its practicality. When using this model to deal with practical problems, multiple covariables are added to the model because it is impossible to know in advance which covariables will affect the results. But the inclusion of some insignificant covariables is almost impossible to avoid. Unfortunately, the usual estimation method is not adequate for the task of deleting the insignificant covariables that cause statistical inferences to become biased. To overcome this defect, we propose a penalised conditional least squares (PCLS) method, which can consistently select the true model. The PCLS estimator is also provided and its asymptotic properties are established. Simulation studies demonstrate that the PCLS method is effective for estimation and variable selection. One practical example is also presented to illustrate the practicability of the PCLS method.     

On the role of local blockchain network features in cryptocurrency price formation

Cryptocurrencies and the underpinning blockchain technology have gained unprecedented public attention recently. In contrast to fiat currencies, transactions of cryptocurrencies, such as Bitcoin and Litecoin, are permanently recorded on distributed ledgers to be seen by the public. As a result, public availability of all cryptocurrency transactions allows us to create a complex network of financial interactions that can be used to study not only the blockchain graph, but also the relationship between various blockchain network features and cryptocurrency risk investment. We introduce a novel concept of chainlets, or blockchain motifs, to utilize this information. Chainlets allow us to evaluate the role of local topological structure of the blockchain on the joint Bitcoin and Litecoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on cryptocurrency price and investment risk. More generally, while statistical aspects of blockchain data analytics remain virtually unexplored, the paper aims to highlight various emerging theoretical, methodological and applied research challenges of blockchain data analysis that will be of interest to the broad statistical community. The Canadian Journal of Statistics 48: 561–581; 2020 © 2020 Statistical Society of Canada     

On aggregation of strongly dependent time series

We consider cross-sectional aggregation of time series with long-range dependence. This question arises for instance from the statistical analysis of networks where aggregation is defined via routing matrices. Asymptotically, aggregation turns out to increase dependence substantially, transforming a hyperbolic decay of autocorrelations to a slowly varying rate. This effect has direct consequences for statistical inference. For instance, unusually slow rates of convergence for nonparametric trend estimators and nonstandard formulas for optimal bandwidths are obtained. The situation changes, when time-dependent aggregation is applied. Suitably chosen time-dependent aggregation schemes can preserve a hyperbolic rate or even eliminate autocorrelations completely.     

Fractional approaches for the distribution of innovation sequence of INAR(1) processes

Abstract

In this paper, we present a fractional decomposition of the probability generating function of the innovation process of the first-order non-negative integer-valued autoregressive [INAR(1)] process to obtain the corresponding probability mass function. We also provide a comprehensive review of integer-valued time series models, based on the concept of thinning operators with geometric-type marginals. In particular, we develop two fractional approaches to obtain the distribution of innovation processes of the INAR(1) model and show that the distribution of the innovations sequence has geometric-type distribution. These approaches are discussed in detail and illustrated through a few examples.     

时间的构成与认知:杰尔的时间人类学理论内核述论

人类的时间观念何以异同是人类学时间研究的一个基本论题。对时间构成与时间认知的理解则左右着人类学家们对此论题的探究。20世纪90年代初,英国人类学家阿尔弗雷德?杰尔在继承与批判既往人类学家之时间论的基础上,综合多学科知识,析分出了作为事件之先后次序的客观时间（“B系列”时间）,作为过去、现在、未来意识的主观时间（“A系列”时间）,以及由主观时间模拟客观时间而生成的时间地图,并基于三者关系构建了一种普世的时间认知机制。杰尔认为,人类的时间认知作为人类基本认知机制运作的一种附带结果,在机制上具有普同性,而时间地图的内容则会随着人类经验与实践而变化,因此,人类学的时间研究应以时间认知机制之普同性为基础,注重探究时间地图之内容差异的社会文化根由。杰尔对时间的构成与认知的讨论是其时间人类学的理论内核,本文对其由来、内涵与缺陷进行了述论,以供后续研究参考。     

Paths towards Family‐friendly Working Time Arrangements: Comparing Workplaces in Different Countries and Industries

Although studies have examined the distribution and conditions of employer‐provided work–family arrangements, we still lack a systematic investigation of how these vary for different countries and industries. Based on the European Working Conditions Survey 2010, this study examines the conditions under which firms provide family‐friendly working time arrangements and what the differences are across four countries (Austria, Denmark, Italy and the UK) and four industries. The impact of employee representatives, employee involvement, manager support and female managers varies across countries and industries because of the institutional environment (prevailing family model, industrial relations) and workforce composition (gender). The impact of employee representatives depends on their co‐determination rights, and the direction of their effect on the prevailing family model (e.g. negative in conservative countries such as Austria) and the gender composition of the workforce (negative in male‐dominated production, but positive in services). Employee involvement in the work organization is significantly positive in Austria and Denmark (both with co‐operative industrial relations), while manager support has the strongest effect in the UK (liberal regime). At the industry level, female supervisors are positively associated with family‐friendly working time arrangements only in the male‐dominated production industry. These findings suggest that the effects of agency variables and their direction vary depending on the institutional context.     

路口通行规则的元胞自动机模拟

目前采用的路口通行规则是,亮绿灯时处于对向的两条车道上的车辆可以同时通行,由于一条车道的直行车辆和另一条车道的左转车辆存在着冲突,交通效率被降低。在上海的一些交通要道已经实施了一种新的交通规则,即每条车道独立轮换通行,本文采用元胞自动机模型,对新老两种路口通行规则的效用进行了模拟研究。结果表明,当车速提高到一定值后,新的规则要优于老的规则。     

A Rhythmic Time for the Digital

ABSTRACT

For the past twenty years, different theoretical accounts in the humanities have either denigrated the digital as precipitating the recession of reality, praised it for constructing new cultural identities, or understood it to empower sensory perception. Broadly speaking, whether positive or negative, most theorists of the digital have tended to focus on a somewhat traditional understanding of technology as separate from the human body, one that enables, extends, addresses or severs, but remains consistently external. This article explores the idea of a rhythmic virtual movement that lurks in the unknown and “unthought” dimensions of experience, in particular it considers how digital art environments can act as an expression of rhythmic time.     

唐诗槐意象的文化与文学观照

唐代沿袭周代以来视槐树为三公之位的文化心理,在长安的街道与宫廷广植槐树。但是,考察唐诗发现,槐的政治意蕴已经退化,从政治符号衍变成了情感符号,并成为一个重要的文学意象。槐意象既是一个时间意象,也是一个空间意象。对于游子而言,槐暗示其与故乡的距离;对于举子而言,槐暗示考试的时间。诗人的时空体验是槐意象的文学意蕴得以建构的内在机制,游宦、赴举等新的文化是外在动因。唐诗中的槐意象传达出流寓者的漂泊情怀、举子的科场心态。     

Time Use by Gender and Quality of Life

Italy has no survey that was specifically designed to measure the degree of quality of life for the population, although certain other surveys exist which contribute useful information on the issue. This paper will concentrate on the potential of using existing sample surveys and on initial studies carried out starting from the Time Use survey conducted by the National Statistical Institute in 1989.Daily activities are the key factor when analysing a person's quality of life, however, these must also be considered in context. First and foremost this context is the household, within which each person carries out more or less defined roles. The roles covered are, in fact, a crucial variable when evaluating each person's quality of life. This angle of obsevation is particularly instructive when seen in terms of developments from a gender standpoint. Interpreting a woman's lifestyle according to the presence of symmeetry of asymmetry of roles, accompanying this analysis with one covering subjective perception of satisfaction as to daily activities, is an essential approach for determining the real satisfaction derived from the different aspects of a person's daily life. In addition to conventional indicators, newly conceived indicators taking into account the division of roles can be of great help when carrying out this kind of study. In this sense the analysis of individual time use in relation to household time use represents a significant step forward when studying quality of life.