Euclidean movement minimization

We consider a class of optimization problems called movement minimization on euclidean plane. Given a set of \(m\) nodes on the plane, the aim is to achieve some specific property by minimum movement of the nodes. We consider two specific properties, namely the connectivity (Con) and realization of a given topology (Topol). By minimum movement, we mean either the sum of all movements (Sum) or the maximum movement (Max). We obtain several approximation algorithms and some hardness results for these four problems. We obtain an \(O(m)\)-factor approximation for ConMax and ConSum and extend some known result on graphical grounds and obtain inapproximability results on the geometrical grounds. For the Topol problems (where the final decoration of the nodes must correspond to a given configuration), we find it much simpler and provide FPTAS for both Max and Sum versions.     

Socio‐cultural Adaptation of Second‐generation Afghans in Iran

The long‐term settlement of Afghan immigrants in Iran, along with their high fertility, has produced an important shift in the composition of their population with the emergence of a “second generation”. This article aims to examine how second‐generation Afghans have adapted to the host society and to what extent their adaptation patterns have correlated with demographic and contextual factors. The data is drawn from the 2010 Afghans Adaptation Survey which covered 520 second‐generation Afghans. Results revealed that second‐generation Afghans have a variety of adaptation patterns. Integration is the most prevalent pattern of adaptation and acculturation (which is observed among 35.8 per cent of respondents) followed by separation (33.3%), assimilation (17.1%) and marginalization (13.8%). Our multivariate analysis showed that such socio‐demographic factors as gender, education, ethnicity, perceived discrimination, family context, neighbourhood characteristics, length and city of residence are associated with their adaptation patterns.

Policy Implications

• Successful implementation of policies and durable solutions for Afghans in Iran rests on the diversity of the adaptation patterns of their second‐generation.
• Restriction on employment opportunities has led to downward assimilation and marginalization of some of the Afghans in Iran. Improvement in labour laws would promote the integration of Afghans in the society.
• Afghan females have relatively better access to a gender‐equitable environment in Iran than they do in Afghanistan, and are less willing to return to their homeland. The Government of Afghanistan should improve service and security provisions for women to ensure their voluntary repatriation.

     

What Level of Statistical Model Should We Use in Small Area Estimation?

If unit‐level data are available, small area estimation (SAE) is usually based on models formulated at the unit level, but they are ultimately used to produce estimates at the area level and thus involve area‐level inferences. This paper investigates the circumstances under which using an area‐level model may be more effective. Linear mixed models (LMMs) fitted using different levels of data are applied in SAE to calculate synthetic estimators and empirical best linear unbiased predictors (EBLUPs). The performance of area‐level models is compared with unit‐level models when both individual and aggregate data are available. A key factor is whether there are substantial contextual effects. Ignoring these effects in unit‐level working models can cause biased estimates of regression parameters. The contextual effects can be automatically accounted for in the area‐level models. Using synthetic and EBLUP techniques, small area estimates based on different levels of LMMs are investigated in this paper by means of a simulation study.     

Mixture Model Analysis of Partially Rank‐Ordered Set Samples: Age Groups of Fish from Length‐Frequency Data

We present a novel methodology for estimating the parameters of a finite mixture model (FMM) based on partially rank‐ordered set (PROS) sampling and use it in a fishery application. A PROS sampling design first selects a simple random sample of fish and creates partially rank‐ordered judgement subsets by dividing units into subsets of prespecified sizes. The final measurements are then obtained from these partially ordered judgement subsets. The traditional expectation–maximization algorithm is not directly applicable for these observations. We propose a suitable expectation–maximization algorithm to estimate the parameters of the FMMs based on PROS samples. We also study the problem of classification of the PROS sample into the components of the FMM. We show that the maximum likelihood estimators based on PROS samples perform substantially better than their simple random sample counterparts even with small samples. The results are used to classify a fish population using the length‐frequency data.     

A New Acceptance Sampling Policy Based on Number of Successive Conforming Items

In an acceptance-sampling plan, where items of an incoming batch of products are inspected one by one, if the number of conforming items between successive non conforming items falls below a lower control threshold, the batch is rejected. If it falls above an upper control threshold, the batch is accepted, and if it lies within the thresholds then the process of inspecting the items continues. The purpose of this article is to develop an optimization model to determine the optimum values of the thresholds such that constraints on the probability of Type I and Type II errors are satisfied. This article starts by developing a Markovian model to derive the expected total cost of the inspection problem containing the costs of acceptance, rejection, and inspection. Then, the optimum values of the thresholds are selected in order to minimize the expected cost. To demonstrate the application of the proposed methodology, perform sensitivity analysis, and compare the performance of the proposed procedure to the one of another method, a numerical example is given at the end and the results are reported.     

A note on the mean residual life function of a coherent system with exchangeable or nonidentical components

This article investigates some properties of the mean residual life function of (n−k+1)-out-of-n systems, when the lifetimes of the system components are independent random variables but not necessarily identically distributed and when the joint distribution of the component lifetimes is exchangeable, extending the results of Asadi and Goliforushani (2008) [On the mean residual life function of coherent systems. IEEE Transactions on Reliability 57 (4) 574-580] for the case of independent and identically distributed components. The extension to a coherent system with exchangeable components is also given.     

Conditional specifications of multivariate pareto and student distributions

A random vector has a multivariate Pareto distribution if one of its univariate conditional distribution is Pareto and some of its marginals are identically distributed.A general method developed in the course of the proof of this result is applied also to characterize the multivariate Student (Cauchy) measure by one univariate Student conditional distribution.     

Estimation of the generalized logistic distribution parameters: Comparative study

The generalized logistic distribution can be considered as a proportional reversed hazard family with the baseline distribution as the logistic distribution. The generalized logistic distribution has been used to model the data with a unimodal density. In this comparison paper, the authors considered the maximum likelihood estimation of the different parameters of a generalized logistic distribution as well as other five estimation procedures. In this paper, we compare the performances of these procedures through an extensive numerical simulation.