Identity Crisis and Integration: The Divergent Attitudes of Iranian Immigrant Men and Women towards Integration into Swedish Society

The main objective of this article is to show the divergent attitudes of Iranian immigrant men and women towards integration into Swedish society.
As several studies have shown, Iranian women have a better chance of adjusting to Western societies than Iranian men. This article discusses the notion that one of the important reasons for this is the determining role of professional position in the life of Iranian immigrants in Sweden.
As a result of the improvement in their work status and therefore an improvement in their social position, Iranian immigrant women now have greater possibilities than Iranian immigrant men to overcome the identity crisis which ordinarily makes ethnic groups and cultural minorities lose their sense of fitting into their new social reality.
This results, in its turn, in the women having a positive attitude towards the new society and increases the extent of their desire for integration into the new society.     

Perception of Identity Threat as the Main Disturbance of Iranian Divorced Women: A Qualitative Study

Postdivorce identity challenges can be experienced differently in societies that underline the lack of normalcy of divorce. Therefore, this study was conducted to explore Iranian divorced women’s perceptions of their identities. A qualitative content analysis method was applied. Participants included 18 divorced women recruited based on purposive sampling. Data were gathered using unstructured interviews, and analyzed via content analysis method. Three categories—stigmatization, separation shock, and remarriage paradox—were extracted, and the main theme was identity threat. Findings illustrate that Iranian divorced women can be considered at risk, and hence, understanding their views is vital for developing context-specific preventive and intervention programs.     

Testing for linearity and convexity of potency curve

Let P(t) be the probability that a subject dies at dose level t or a unit fails at stress level t,then the Bayesian methodology is used to test (i) P(t) is straight line and (ii) P(t) is convex function (concave function).     

Pareto analysis for the lifetime performance index of products on the basis of progressively first-failure-censored batches under balanced symmetric and asymmetric loss functions

One of the most important topics in manufacturing industries is the evaluation of performance lifetimes of products. Based on a given lifetime performance index, this paper deals with evaluating the performance of a process subject to a given lower specification limit. We confine ourselves to the progressively first-failure-censored data coming from a common Pareto distribution. With both the Bayesian and the non-Bayesian approaches being investigated here, we pay more attention to Bayesian estimators under balanced type loss functions. The results are presented under the balanced versions of two well-known loss functions, namely the squared error loss and the Varian's linear-exponential (LINEX) loss. Moreover, based on the Bayesian and the non-Bayesian approaches, the problem of testing hypotheses on the lifetime performance index is studied. Also, a simulation study is performed to assess the obtained results. Finally, two illustrative examples are given.     

Entropy properties of record statistics

Record values can be viewed as order statistics from a sample whose size is determined by the values and the order of occurrence of observations. They are closely connected with the occurrence times of a corresponding non-homogenous Poisson process and reliability theory. In this paper, the information properties of record values are presented based on Shannon information. Several upper and lower bounds for the entropy of record values are obtained. It is shown that, the mutual information between record values is distribution free and is computable using the distribution of the record values of the sequence from the uniform distribution.     

On the Optimal Parameters for Reconstruction and Forecasting in Singular Spectrum Analysis

There are two main parameters in Singular Spectrum Analysis (SSA). The aim of this study is to determine whether the optimal values of these parameters are different for reconstruction and forecasting stages, and if those are worth the extra computational effort and time which they require. Here, we evaluate these issues using simulation study.     

Estimation for the Parameters of Generalized Half-normal Distribution Based on Progressive Type-I Interval Censoring

Based on progressively Type-I interval censored sample, the problem of estimating unknown parameters of a two parameter generalized half-normal(GHN) distribution is considered. Different methods of estimation are discussed. They include the maximum likelihood estimation, midpoint approximation method, approximate maximum likelihood estimation, method of moments, and estimation based on probability plot. Several Bayesian estimates with respect to different symmetric and asymmetric loss functions such as squared error, LINEX, and general entropy is calculated. The Lindley’s approximation method is applied to determine Bayesian estimates. Monte Carlo simulations are performed to compare the performances of the different methods. Finally, analysis is also carried out for a real dataset.     

A Feasibility Study of Implementing the Policies on Increasing Birth Rate with an Emphasis on Socio-economic Status: A Case Study of Kermanshah Metropolis,Western Iran

Population and development have a mutual relationship, and more to the point, lack of sufficient knowledge on population development and fertility can lead to the presentation of inappropriate population plans in such a way that they may turn out to be useless and ineffective even in the event of implementation. So, the present study aimed to delve into the feasibility of implementing the new governmental policies on increasing birth rate with an emphasis on the socioeconomic status in Kermanshah Metropolis, Iran. To evaluate poverty and fertility in Kermanshah Metropolis, the present cross-sectional study used the latest statistics obtained from the Statistical Center of Iran (2011), and as for the data analysis, such tests in Arc/GIS and SPSS 20 software. The results of the present study showed that the spatial patterns of poverty and fertility were formed in clusters across the city, and the results of variance analysis of the relationship between the variables of fertility and poverty demonstrated that there was a significant difference between the selected neighborhoods in terms of the variables of poverty and total fertility (P < 0.001). Furthermore, the spatial autocorrelations of fertility and poverty in Kermanshah were positive and showed that the spatial means and standard distances of poverty and fertility were overlapping. Not all districts and urban neighborhoods were equal in the total fertility rate. So, given the societal classes’ different socioeconomic and cultural status across different neighborhoods, the government’s new approaches to increasing birthrate cannot be applied to all classes throughout Kermanshah Metropolis.

     

Lifetime performance index based on ranked set sampling

In this article, we assume that the lifetimes of products follow a one-parameter exponential distribution and use both conjugate and Jeffreys prior distributions for finding a Bayes estimator based on the RSS scheme for lifetime performance index CL. We also obtained maximum likelihood and adhac estimators for CL. Monte Carlo simulation study is done for comparing the obtained estimators in two sampling schemes SRS and RSS. Fisher information has been utilized to obtain lower confidence bound of CL for both schemes in asymptotically state and use this bounds for hypothesis testing of CL.     

A two-step robust estimation of the process mean using M-estimator

Parameter estimation is the first step in constructing control charts. One of these parameters is the process mean. The classical estimators of the process mean are sensitive to the presence of outlying data and subgroups which contaminate the whole data. In existing robust estimators for the process mean, the effects of the presence of the individual outliers are being considered, while, in this paper, a robust estimator is being proposed to reduce the effect of outlying subgroups as well as the individual outliers within a subgroup. The proposed estimator was compared with some classical and robust estimators of the process mean. Although, its relative efficiency is fourth among the estimators tested, its robustness and efficiency are large when the outlying subgroups are present. Evaluation of the results indicated that the proposed estimator is less sensitive to the presence of outliers and the process mean performs well when there are no individual outliers or outlying subgroups.