Modelling the spread in space and time of an airborne plant disease

Summary.  A spatiotemporal model is developed to analyse epidemics of airborne plant diseases which are spread by spores. The observations consist of measurements of the severity of disease at different times, different locations in the horizontal plane and different heights in the vegetal cover. The model describes the joint distribution of the occurrence and the severity of the disease. The three-dimensional dispersal of spores is modelled by combining a horizontal and a vertical dispersal function. Maximum likelihood combined with a parametric bootstrap is suggested to estimate the model parameters and the uncertainty that is attached to them. The spatiotemporal model is used to analyse a yellow rust epidemic in a wheatfield. In the analysis we pay particular attention to the selection and the estimation of the dispersal functions.     

Refusal Bias in the Estimation of HIV Prevalence

In 2007, UNAIDS corrected estimates of global HIV prevalence downward from 40 million to 33 million based on a methodological shift from sentinel surveillance to population-based surveys. Since then, population-based surveys are considered the gold standard for estimating HIV prevalence. However, prevalence rates based on representative surveys may be biased because of nonresponse. This article investigates one potential source of nonresponse bias: refusal to participate in the HIV test. We use the identity of randomly assigned interviewers to identify the participation effect and estimate HIV prevalence rates corrected for unobservable characteristics with a Heckman selection model. The analysis is based on a survey of 1,992 individuals in urban Namibia, which included an HIV test. We find that the bias resulting from refusal is not significant for the overall sample. However, a detailed analysis using kernel density estimates shows that the bias is substantial for the younger and the poorer population. Nonparticipants in these subsamples are estimated to be three times more likely to be HIV-positive than participants. The difference is particularly pronounced for women. Prevalence rates that ignore this selection effect may be seriously biased for specific target groups, leading to misallocation of resources for prevention and treatment.     

Psychometric Evaluation of a Serbian Version of the Subjective Happiness Scale

The main aim of this research was to examine the psychometric properties of the Subjective Happiness Scale (SHS; Lyubomirsky and Lepper in Soc Indic Res 46:137–155, 1999) in a sample of young adults in Serbia (N = 605, mean age = 21.99). The SHS demonstrated adequate internal consistency reliability and homogeneity. Exploratory and Confirmatory factor analyses supported the unidimensional structure of the SHS. The results provided support for the convergent validity of the SHS, by significant correlations with measures of subjective well-being (life satisfaction, positive and negative affect, emotional distress), positive expectations (optimism and self-efficacy), meaning in life and personality traits (extraversion and neuroticism). As compared to the Satisfaction with Life Scale, the SHS showed significantly higher correlations with measures of emotional states and personality traits. Hierarchical regression analyses showed that the SHS had incremental validity over and above subjective well-being and personality traits in predicting emotional distress and meaning in life.     

Fast Random Number Generation Using 128-Bit Multimedia Extension Registers on Pentium Class Machines

In this article, it is shown how 128-bit SSE2 multimedia extension registers, present in Pentium IV class 32-bit processors, may be used to generate random numbers at several times greater speed then when regular general purpose registers are used. In particular, a 128-bit algorithm is presented for the Marsaglia MWC1616 generator from the DIEHARD battery of random number generator tests, and its performance is compared to that of the conventional approach.     

On Shifted Geometric INAR(1) Models Based on Geometric Counting Series

Two types of shifted geometric integer valued autoregressive models of order one (SGINAR(1)) are proposed. Both are based on the thinning operator generated by counting series of i.i.d. geometric random variables. Their correlation properties are derived and compared. Also, regression and conditional variance are considered. Nonparametric estimators of model parameters are obtained and their asymptotic characterizations are given. Finally, these two models are applied to a real-life data set and they are compared to some referent INAR(1) models.     

The Marshall-Olkin Fréchet Distribution

We introduce a new distribution, namely Marshall–Olkin Fréchet distribution. The probability density and hazard rate functions are derived and their shape properties are considered. Expressions for the nth moments are given. Various results with respect to quantiles, Rényi entropy and order statistics are obtained. The unknown parameters of the new distribution are estimated using the maximum likelihood estimation method adopting three different iterative procedures. The model is applied on a real data set on survival times.

[Supplementary materials are available for this article. Go to the publisher's online edition of Communications in Statistics—Theory and Methods for the following free supplemental resource: A file that will allow the random variables from MOF distribution to be generated.]     

Estimation in a bivariate integer-valued autoregressive process

ABSTRACT

A bivariate integer-valued autoregressive time series model is presented. The model structure is based on binomial thinning. The unconditional and conditional first and second moments are considered. Correlation structure of marginal processes is shown to be analogous to the ARMA(2, 1) model. Some estimation methods such as the Yule–Walker and conditional least squares are considered and the asymptotic distributions of the obtained estimators are derived. Comparison between bivariate model with binomial thinning and bivariate model with negative binomial thinning is given.     

On some moving-average processes with exponentially distributed innovations

Summary In this paper we discusse the stationary sequence of random variables which are formed from an independent identically distributed sequence, according to the moving-average model of ordern. Some properties of the process are considered. The joint bivariate exponential distribution is given, as well as the distribution of the sum.     

Work, employment and mental health in Europe

In May 2004 the World Health Organization (WHO European Region) called a consultation meeting of its Collaborating Centres in Occupational Health to discuss mental health in the workplace. The meeting took place in Copenhagen. This paper presents an interpretation of the discussion that took place and the thinking that developed as a result. It was argued that increased interest and research and improved practice in the area of occupational mental health are required to promote good mental health in the European population. A framework of risk management and prevention based on sound evidence and good understanding could provide the basis for the translation of existing research knowledge into effective practice.