GEE-based zero-inflated generalized Poisson model for clustered over or under-dispersed count data

The zero-inflated regression models such as zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB) or zero-inflated generalized Poisson (ZIGP) regression models can model the count data with excess zeros. The ZINB model can handle over-dispersed and the ZIGP model can handle the over or under-dispersed count data with excess zeros as well. Moreover, the count data may be correlated because of data collection procedure or special study design. The clustered sampling approach is one of the examples in which the correlation among subjects could be defined. In such situations, a marginal model using generalized estimating equation (GEE) approach can incorporate these correlations and lead up to the relationships at the population level. In this study, the GEE-based zero-inflated generalized Poisson regression model was proposed to fit over and under-dispersed clustered count data with excess zeros.     

Asymptotic properties of the kernel mode estimator under twice censorship model

In this article, we study the asymptotic properties of the kernel estimator of the mode and density function when the data are twice censored. More specifically, we first establish a strong uniform consistency over a compact set with a rate of the kernel density estimator and then we give the consistency with rate and asymptotic normality for the kernel mode estimator. An application to confidence bands is given.     

Forecasting before,during, and after recession with singular spectrum analysis

The aim of this research is to apply the singular spectrum analysis (SSA) technique, which is a relatively new and powerful technique in time series analysis and forecasting, to forecast the 2008 UK recession, using eight economic time series. These time series were selected as they represent the most important economic indicators in the UK. The ability to understand the underlying structure of these series and to quickly identify turning points such as the on-set of the recent recession is of key interest to users. In recent years, the SSA technique has been further developed and applied to many practical problems. Hence, these series will provide an ideal practical test of the potential benefits from SSA during one of the most challenging periods for econometric analyses of recent years. The results are compared with those obtained using the ARIMA and Holt–Winters models as these methods are currently used as standard forecasting methods in the Office for National Statistics in the UK.     

Linear rank tests for homogeneity against ordered alternatives in anova and anocova

A unified method of constructing rank tests for homogeneity against ordered alternatives in unbalanced analysis of variance and analysis of covariance is considered. The relationship between these tests with some of the existing methods are studied. The normal theory likelihood ratio tests are also derived and the asymptotic relative efficiency comparisons, in Pitman sense, of the rank tests with respect to the likelihood ratio tests are carried out.     

Distribution-free tests in randomized blocks

Classes of distribution-free tests are proposed for testing homogeneity against order restricted as well as unrestricted alternatives in randomized block designs with multiple observations per cell. Allowing for different interblock scoring schemes, these tests are constructed based on the method of within block rankings. Asymptotic distributions (cell sizes tending to infinity) of these tests are derived under the assumption of homogeneity. The Pitman asymptotic relative efficiencies relative to the least squares statistics are studied. It is shown that when blocks are governed by different distributions, adaptive choice of scores within each block results in asymptotically more efficient tests as compared with methods that ignore such information. Monte Carlo simulations of selected designs indicate that the method of within block rankings is more power robust with respect to differing block distributions.     

A class of rank tests for interaction in two-way layouts

A class of aligned rank order tests for interaction in two-way layouts is considered. The technique is based on application of the existing nonparametric techniques for one-way layouts to the transformed observations. It is shown that the asymptotic properties of these techniques are preserved after alignment. Furthermore, asymptotic relative efficiency comparisons are made with some of the competing tests. Finally, we demonstrate that our technique can be used to test for higher-order interactions in general multi-factor layouts.     

On approximating distribution of the quadratic discriminant function

The quadratic discriminant function (QDF) with known parameters has been represented in terms of a weighted sum of independent noncentral chi-square variables. To approximate the density function of the QDF as m-dimensional exponential family, its moments in each order have been calculated. This is done using the recursive formula for the moments via the Stein's identity in the exponential family. We validate the performance of our method using simulation study and compare with other methods in the literature based on the real data. The finding results reveal better estimation of misclassification probabilities, and less computation time with our method.     

Quality of Life of Afghan Immigrants in Tehran city

By 2015, there were more than two million Afghan immigrants, both legal and illegal, living in Iran. Although, over the recent years, there has been a growing interest among social scientists, policymakers and national and international institutes in investigation of the quality of life (QoL) of immigrants, research on the QoL of Afghan immigrants in Iran is still in its infancy. The present article aims to study the QoL of Afghan immigrants in Iran and identify its influential dimensions and factors. This study relies on a perception survey of 347 Afghan households in Tehran city. Based on the 5‐point Likert Scale, the mean of overall life satisfaction of the Afghan immigrants was found as 3.22, which shows satisfactory QoL of Afghan immigrants in Iran. The highest level of satisfaction, with a mean value of 3.96, is related to public transport access followed by satisfaction in social relations with friends, relatives and fellow immigrants living in Iran, and access to cultural centres such as the mosque, library, and cinema. The lowest level of satisfaction, with a mean value of 1.90, was seen at border services like entry and exit from Iran, followed by the Iranian government policy towards Afghan refugees, and saving abilities. In addition, the most important predictors of immigrants' QoL include indicators of health, security, work status, and income, which are closely interrelated with the main reasons for Afghans' immigration to Iran. After immigration to Iran, the QoL status of the immigrants has improved significantly, especially in the fields of security and education; nevertheless, their employment in jobs with low skill and income, along with the decrease in the economic growth of Iran over the recent years, have caused problems for the economic and financial status of the immigrants. The results and findings of this study will be useful for designing and implementing plans and policies necessary to improve QoL of Afghan immigrants in Iran.     

Is there a causal relationship between oil prices and tourist arrivals?

This application note investigates the causal relationship between oil price and tourist arrivals to further explain the impact of oil price volatility on tourism-related economic activities. The analysis itself considers the time domain, frequency domain and information theory domain perspectives. Data relating to US and nine European countries are exploited in this paper with causality tests which include time domain, frequency domain, and Convergent Cross Mapping (CCM). The CCM approach is nonparametric and therefore not restricted by assumptions. We contribute to existing research through the successful and introductory application of an advanced method, and via the uncovering of significant causal links from oil prices to tourist arrivals.     

AN ALTERNATIVE VARIANCE-REDUCTION STRATEGY FOR RSM SIMULATION STUDIES

In the previous paper, Cooley and Houck [1] examined the simultaneous use of common and antithetic random number streams as a variance-reduction strategy for simulation studies employing response surface methodology (RSM). Our paper supplements their work and further explores pseudorandom number assignments in response surface designs. Specifically, an alternative strategy for assigning pseudorandom numbers is proposed; this strategy is more efficient than that given by Cooley and Houck, especially when more than two factors are involved.