The effect of fat-tailed error terms on the properties of systemwise RESET test

The small sample properties of the systemwise RESET (Regression Specification Error Test) test for functional misspecification are investigated using normal and non-normal error terms. When using normally distributed or less heavy tailed error terms, we find the Rao's multivariate F-test to be best among all other alternative test methods (i.e. Wald, Lagrange Multiplier and Likelihood Ratio). Using the bootstrap critical values, however, all test methods perform satisfactorily in almost all situations. However, the test methods perform extremely badly (even the RAO test) when the error terms are very heavy tailed.     

A case study of urban ecological networks and a sustainable city: Tehran’s metropolitan area

The aim of this study is to propose the application of landscape ecology in planning urban ecological networks to conserve nature in urban landscapes and to develop a sustainable use of urban lands. Compared to the classical planning approach based on socio-economic land suitability, the principles of landscape ecology are helpful simultaneously conserving the ecological processes of landscapes and their steady changes. This approach could help in defining sustainable landscape development, aiming for a balance between both physical and natural systems in urban areas. This research is focused on the ecological networks in Tehran’s metropolitan area as a case study to provide a model for network planning in other urban areas, where urbanization seriously threats the natural environment. In concluding this research, the spatial structure and function of the area are studied and categorized based on the patch-corridor-matrix model. The paper concludes with methods of intervention and suggestions for the structural and functional improvement of urban landscapes towards achieving a more sustainable form of land use planning.     

On simulating truncated skewed Cauchy random variables

Shirvani and Soltani suggested a method for characterizing and simulating one-sided truncated Cauchy random variables. For simulation, that involves solving a nonlinear transformation in each iteration. Here, we propose an alternative method to generate Cauchy random variables. Our method is more general (e.g., incorporates one-sided and two-sided truncations) and does not involve solving any equation. It can be implemented even using a hand calculator.     

Estimation with the lognormal distribution on the basis of records

Record scheme is a method to reduce the total time on test of an experiment. In this scheme, items are sequentially observed and only values smaller than all previous ones are recorded. In some situations, when the experiments are time-consuming and sometimes the items are lost during the experiment, the record scheme dominates the usual random sample scheme [M. Doostparast and N. Balakrishnan, Optimal sample size for record data and associated cost analysis for exponential distribution, J. Statist. Comput. Simul. 80(12) (2010), pp. 1389–1401]. Estimation of the mean of an exponential distribution based on record data has been treated by Samaniego and Whitaker [On estimating population characteristics from record breaking observations I. Parametric results, Naval Res. Logist. Q. 33 (1986), pp. 531–543] and Doostparast [A note on estimation based on record data, Metrika 69 (2009), pp. 69–80]. The lognormal distribution is used in a wide range of applications when the multiplicative scale is appropriate and the log-transformation removes the skew and brings about symmetry of the data distribution [N.T. Longford, Inference with the lognormal distribution, J. Statist. Plann. Inference 139 (2009), pp. 2329–2340]. In this paper, point estimates as well as confidence intervals for the unknown parameters are obtained. This will also be addressed by the Bayesian point of view. To carry out the performance of the estimators obtained, a simulation study is conducted. For illustration proposes, a real data set, due to Lawless [Statistical Models and Methods for Lifetime Data, 2nd ed., John Wiley & Sons, New York, 2003], is analysed using the procedures obtained.     

Some results on conditional expectations of lower record values

In this paper, we propose a measure for obtaining the expectation of time between two lower k-records under the condition that the greater one is given. Several properties of the proposed measure are derived. Some characterization results and stochastic comparisons based on the new measure are also provided.     

On characterizations of the generalized Pareto distributions based on progressively censored order statistics

It is well-known, in the literature, that most of the characterization results on exponential distribution are based on the solution of Cauchy functional equation and integrated Cauchy functional equation. In the present paper, we consider the functional equation $$F(x) = F(xy) + F(xQ(y)), \quad x, xQ(y) \in [0, \theta),\; y \in [0,1],$$ where F and Q satisfy certain conditions, to give some new characterization results on the generalized Pareto distributions based on progressively Type-II right censored order statistics. We prove the main results without restricting to distributions that are absolutely continuous with respect to Lebesgue measure.     

The odd power cauchy family of distributions: properties,regression models and applications

We study some mathematical properties of a new generator of continuous distributions with one extra parameter called the odd power Cauchy family including asymptotics, linear representation, moments, quantile and generating functions, entropies, order statistics and extreme values. We introduce two bivariate extensions of the new family. The maximum likelihood method is discussed to estimate the model parameters by means of a Monte Carlo simulation study. We define a new log-odd power Cauchy–Weibull regression model. The usefulness of the proposed models is proved empirically by means of three real data sets.     

Quality of Life in College Students with and without Social Phobia

Prior studies demonstrating quality of life impairment in phobia and anxiety disorders have relied upon epidemiological samples or clinical data. Using the same quality of life scale, the Short Form 36-item Health Survey (SF-36), in Iranian college students allowed us to study the impact of social phobia (SP) on quality of life among the college students. This report summarizes findings from a cross sectional study on Iranian students with social phobia studying at Shahed University. Quality of life was measured using the Short Form 36-item Health Survey (SF-36) which is a widely used and valid questionnaire to measure quality of life in cross-sectional and longitudinal studies. Three standard instruments were used to measure social phobia severity, namely Social Phobia Inventory, Social Interaction Anxiety Scale, and Brief version of the Fear of Negative Evaluation Scale. The sample consisted of 202 college students, 72 with SP and 130 without SP. The main finding of this study was that students with social phobia reported significantly lower quality of life, particularly in general health (P = 0.02), vitality (P < 0.0001), social functioning (P < 0.0001), role functioning—emotional (P < 0.0001), and Mental health (P = 0.001) dimensions. Standardized summed scores for mental health components of the SF-36 showed that 36.2% of all the s with SP were severely impaired while 16.0% of the students in control croup were severely impaired. Findings demonstrated that Iranian socially anxious college students reported extensive functional disability, and lower well-being compared to those without SP. These findings should encourage education officers to implement systematic efforts to prevent and treat social anxiety among students.     

Predictive analysis for joint progressive censoring plans: a Bayesian approach

Comparative lifetime experiments are of particular importance in production processes when one wishes to determine the relative merits of several competing products with regard to their reliability. This paper confines itself to the data obtained by running a joint progressive Type-II censoring plan on samples in a combined manner. The problem of Bayesian predicting failure times of surviving units is discussed in details when parent populations are exponential. Two real data sets are analyzed in order to illustrate all the inferential procedures developed here. When destructive experiments under a censoring scheme finished, the researchers are usually interested to estimate remaining lifetimes of surviving units for sequel experiments. Findings of this paper are useful for these purposes specially when samples are non-homogeneous such as those taken from industrial storages.     

EM algorithm for mixture of skew-normal distributions fitted to grouped data

Grouped data are frequently used in several fields of study. In this work, we use the expectation-maximization (EM) algorithm for fitting the skew-normal (SN) mixture model to the grouped data. Implementing the EM algorithm requires computing the one-dimensional integrals for each group or class. Our simulation study and real data analyses reveal that the EM algorithm not only always converges but also can be implemented in just a few seconds even when the number of components is large, contrary to the Bayesian paradigm that is computationally expensive. The accuracy of the EM algorithm and superiority of the SN mixture model over the traditional normal mixture model in modelling grouped data are demonstrated through the simulation and three real data illustrations. For implementing the EM algorithm, we use the package called ForestFit developed for R environment available at https://cran.r-project.org/web/packages/ForestFit/index.html.