Periodic integer-valued GARCH(1, 1) model

This article deals with some probabilistic and statistical properties of a periodic integer-valued GARCH(1,1) model. Necessary and sufficient conditions for the periodical stationary, both in mean and second order, are established. The closed-forms of the mean and the second moment are, under these conditions, obtained. The condition of the existence of higher moment orders and their explicit formula in terms of the parameters are established. The autocovariance structure is studied, while providing the closed-form of the periodic autocorrelation function. The Yule–Walker and the likelihood estimations of the underlying parameters are obtained. A simulation study and an application on real dataset are provided.     

An On-Line Estimation Algorithm for Periodic Autoregressive Models

This paper develops an on-line estimation algorithm for periodic autoregressive models (PAR). Indeed, we provide an adaptation of the well known recursive least squares algorithm (RLS), which has been successfully applied to classical autoregressive models (AR), to deal with PAR models. The obtained estimators are shown to be asymptotically efficient under mild conditions. Moreover, the performance of the periodic least squares algorithm (PRLS) is assessed via an intensive simulation study.     

Post-Political Transitions in Arab Spring Countries: The Challenges

This paper aims at examining the impact of political transitions on democracy, corruption and growth in countries which knew democratic changes. The results of our study indicate that these changes positively affect implementation of democratic principles, the struggle against corruption and economic growth. We examined also the case of the Arab spring countries focusing on the main political and socio-economic challenges and most importantly the religious challenge which is a characteristic of these countries. Indeed, religion may be considered as a relevant variable in these transitions and consequently it is very difficult to claim short-term or long-term triumph of these transitions as Arabs are now in a political boiling phase where religion may gather unexpected results.     

Adjusting for covariates in non-inferiority studies with margins defined as risk differences

Adjusting for covariates makes efficient use of data and can improve the precision of study results or even reduce sample sizes. There is no easy way to adjust for covariates in a non-inferiority study for which the margin is defined as a risk difference. Adjustment is straightforward on the logit scale, but reviews of clinical studies suggest that the analysis is more often conducted on the more interpretable risk-difference scale. We examined four methods that allow for adjustment on the risk-difference scale: stratified analysis with Cochran-Mantel-Haenszel (CMH) weights, binomial regression with an identity link, the use of a Taylor approximation to convert results from the logit to the risk-difference scale and converting the risk-difference margin to the odds-ratio scale. These methods were compared using simulated data based on trials in HIV. We found that the CMH had the best trade-off between increased efficiency in the presence of predictive covariates and problems in analysis at extreme response rates. These results were shared with regulatory agencies in Europe and the USA, and the advice received is described.     

Screening for recommended antenatal risk factors: How long does it take?

Background

Detection and management of antenatal risk factors is critical for quality care.

Household and Contextual Indicators of Poverty in Tunisia: A Multilevel Analysis

Using micro data from the 2010 National Survey on Households’ Budget, Consumption and Standard of Living, this study aims to investigate main factors contributing to poverty distribution, one of the most severe socioeconomic problems in Tunisia. To this end, we use a multilevel Logit model and a multilevel mixed linear model to simultaneously analyze the micro-level (household) and macro-level (governorate) factors that might affect the household poverty status. Household size, household composition, occupation, education levels, the gender of the household head and the number of earner by household variables were assessed at the micro-level. Unemployment rate, poverty rate, industrial and agriculture parts and the migration are included to control the effect of contextual effects. Our findings showed that the likelihood of household being poor is positively and significantly related to household size, more children and lower education level. Extreme poverty is more likely to occur in rural than urban areas. Macro-level analyses indicated that greater neighbourhood unemployment rate was associated with higher odds of poverty, while greater industrial agglomeration and migration balance were associated with reduced odds of poverty.     

Estimation of generalized exponential distribution based on an adaptive progressively type-II censored sample

In this paper, based on an adaptive Type-II progressively censored sample from the generalized exponential distribution, the maximum likelihood and Bayesian estimators are derived for the unknown parameters as well as the reliability and hazard functions. Also, the approximate confidence intervals of the unknown parameters, and the reliability and hazard functions are calculated. Markov chain Monte Carlo method is applied to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. Moreover, results from simulation studies assessing the performance of our proposed method are included. Finally, an illustrative example using real data set is presented for illustrating all the inferential procedures developed here.     

On the b-coloring of tight graphs

A coloring c of a graph \(G=(V,E)\) is a b -coloring if for every color i there is a vertex, say w(i), of color i whose neighborhood intersects every other color class. The vertex w(i) is called a b-dominating vertex of color i. The b -chromatic number of a graph G, denoted by b(G), is the largest integer k such that G admits a b-coloring with k colors. Let m(G) be the largest integer m such that G has at least m vertices of degree at least \(m-1\). A graph G is tight if it has exactly m(G) vertices of degree \(m(G)-1\), and any other vertex has degree at most \(m(G)-2\). In this paper, we show that the b-chromatic number of tight graphs with girth at least 8 is at least \(m(G)-1\) and characterize the graphs G such that \(b(G)=m(G)\). Lin and Chang (2013) conjectured that the b-chromatic number of any graph in \(\mathcal {B}_{m}\) is m or \(m-1\) where \(\mathcal {B}_{m}\) is the class of tight bipartite graphs \((D,D{^\prime })\) of girth 6 such that D is the set of vertices of degree \(m-1\). We verify the conjecture of Lin and Chang for some subclass of \(\mathcal {B}_{m}\), and we give a lower bound for any graph in \(\mathcal {B}_{m}\).     

The Role of Religiosity on the Relationship Between Materialism and Fashion Clothing Consumption Among Malaysian Generation Y Consumers

Religiosity is a significant cultural force influencing various dimensions of consumer behaviours; however, its role in the literature on fashion clothing remains unclear. To rectify this paucity of information, this study explores the relationship between religiosity, materialism and fashion clothing involvement (FCI); and religiosity, materialism and fashion clothing purchase involvement (FCPI). Using a sample of 282 Malaysian Generation Y consumers, it employs a positivist research approach, comprising of a quantitative basis of enquiry, and gathered data via survey questionnaires. The research findings show that religiosity moderates the relationship between materialism and FCI, as well as materialism and FCPI, where an individual’s religiosity is inversely associated with FCPI. Another finding is the importance of FCI in mediating the relationship between materialism and FCPI, plus the significance of mediated moderation and its effects on the relationship between materialism and FCPI. The findings reinforce the role of religiosity in consumer involvement in fashion clothing and fashion clothing purchase trends. Recognition of this significant construct and its importance may enable marketers to develop more sophisticated positioning strategies.