Comparisons of methods of estimation for a pareto distribution of the first kind

This paper compares methods of estimation for the parameters of a Pareto distribution of the first kind to determine which method provides the better estimates when the observations are censored, The unweighted least squares (LS) and the maximum likelihood estimates (MLE) are presented for both censored and uncensored data. The MLE's are obtained using two methods, In the first, called the ML method, it is shown that log-likelihood is maximized when the scale parameter is the minimum sample value. In the second method, called the modified ML (MML) method, the estimates are found by utilizing the maximum likelihood value of the shape parameter in terms of the scale parameter and the equation for the mean of the first order statistic as a function of both parameters. Since censored data often occur in applications, we study two types of censoring for their effects on the methods of estimation: Type II censoring and multiple random censoring. In this study we consider different sample sizes and several values of the true shape and scale parameters.

Comparisons are made in terms of bias and the mean squared error of the estimates. We propose that the LS method be generally preferred over the ML and MML methods for estimating the Pareto parameter γ for all sample sizes, all values of the parameter and for both complete and censored samples. In many cases, however, the ML estimates are comparable in their efficiency, so that either estimator can effectively be used. For estimating the parameter α, the LS method is also generally preferred for smaller values of the parameter (α ≤4). For the larger values of the parameter, and for censored samples, the MML method appears superior to the other methods with a slight advantage over the LS method. For larger values of the parameter α, for censored samples and all methods, underestimation can be a problem.     

Selected Ranked Set Sampling

This paper proposes a sampling procedure called selected ranked set sampling (SRSS), in which only selected observations from a ranked set sample (RSS) are measured. This paper describes the optimal linear estimation of location and scale parameters based on SRSS, and for some distributions it presents the required tables for optimal selections. For these distributions, the optimal SRSS estimators are compared with the other popular simple random sample (SRS) and RSS estimators. In every situation the estimators based on SRSS are found advantageous at least in some respect, compared to those obtained from SRS or RSS. The SRSS method with errors in ranking is also described. The relative precision of the estimator of the population mean is investigated for different degrees of correlations between the actual and erroneous ranking. The paper reports the minimum value of the correlation coefficient between the actual and the erroneous ranking required for achieving better precision with respect to the usual SRS estimator and with respect to the RSS estimator.     

Integration policy in Singapore: a transnational inclusion approach

A number of models of integration have been developed to highlight the experiences of immigration and integration in the Western world. However, the existing models do not adequately capture the complexities of contemporary international immigration and integration, especially the integration process in the light of migrant transnationalism in Asia. This study examines the models of integration through a case study of Singapore. This paper introduces a new concept ‘transnational inclusion’ to conceptualize Singapore's initiative to embrace its transnational global Singaporeans as well as its transnational immigrants, estimated to make up one-fourth of the total population. The paper shows that a transnational inclusion model of integration can provide better insights into the dynamics of transnationalism and integration in today's complex migration scenario. We point to Singapore's integration approach that regards integrating migrants into the different spheres of the society as a process rather than an end.     

Spatio-temporal modeling of infectious disease dynamics

A stochastic model, which is well suited to capture space–time dependence of an infectious disease, was employed in this study to describe the underlying spatial and temporal pattern of measles in Barisal Division, Bangladesh. The model has two components: an endemic component and an epidemic component; weights are used in the epidemic component for better accounting of the disease spread into different geographical regions. We illustrate our findings using a data set of monthly measles counts in the six districts of Barisal, from January 2000 to August 2009, collected from the Expanded Program on Immunization, Bangladesh. The negative binomial model with both the seasonal and autoregressive components was found to be suitable for capturing space–time dependence of measles in Barisal. Analyses were done using general optimization routines, which provided the maximum likelihood estimates with the corresponding standard errors.     

Shrinkage and pretest estimators for longitudinal data analysis under partially linear models

In this paper, we develop marginal analysis methods for longitudinal data under partially linear models. We employ the pretest and shrinkage estimation procedures to estimate the mean response parameters as well as the association parameters, which may be subject to certain restrictions. We provide the analytic expressions for the asymptotic biases and risks of the proposed estimators, and investigate their relative performance to the unrestricted semiparametric least-squares estimator (USLSE). We show that if the dimension of association parameters exceeds two, the risk of the shrinkage estimators is strictly less than that of the USLSE in most of the parameter space. On the other hand, the risk of the pretest estimator depends on the validity of the restrictions of association parameters. A simulation study is conducted to evaluate the performance of the proposed estimators relative to that of the USLSE. A real data example is applied to illustrate the practical usefulness of the proposed estimation procedures.     

Comparison of location parameters of two exponential distributions when scale parameters are different and unknown

Letx _i(1)≤x _i(2)≤…≤x _i(r_i) be the right-censored samples of sizesn _i from theith exponential distributions $\sigma _i^{ - 1} exp\{ - (x - \mu _i )\sigma _i^{ - 1} \} ,i = 1,2$ where μ_i and σ_i are the unknown location and scale parameters respectively. This paper deals with the posteriori distribution of the difference between the two location parameters, namely μ₂-μ₁, which may be represented in the form $\mu _2 - \mu _1 \mathop = \limits^\mathcal{D} x_{2(1)} - x_{1(1)} + F_1 \sin \theta - F_2 \cos \theta $ where $\mathop = \limits^\mathcal{D} $ stands for equal in distribution,F _i stands for the central F-variable with [2,2(r _i?1)] degrees of freedom and $\tan \theta = \frac{{n_2 s_{x1} }}{{n_1 s_{x2} }}, s_{x1} = (r_1 - 1)^{ - 1} \left\{ {\sum\limits_{j = 1}^{r_i - 1} {(n_i - j)(x_{i(j + 1)} - x_{i(j)} )} } \right\}$ The paper also derives the distribution of the statisticV=F ₁ sin σ?F ₂ cos σ and tables of critical values of theV-statistic are provided for the 5% level of significance and selected degrees of freedom.     

Structural social work and the compatibility of NGO approaches: a case analysis of Bangladesh Rural Advancement Committee (BRAC)

This article offers a comparative analysis between the ideological orientation of structural social work (SSW) and the programmatic orientation of the Bangladesh Rural Advancement Committee (BRAC). SSW sees social problems as arising from specific socio-economic contexts rather than from the failings of individuals. This perspective recognises that patriarchy is a central feature of life in Bangladesh. BRAC analyses poverty, broadly defined, from a perspective that is political, making use of feminist principles. By assessing SSW as it pertains to the programme coverage of BRAC, this article presents the consistencies and inconsistencies of the approaches. Yet, SSW and BRAC share a common objective of shifting the locus of power to facilitate the empowerment of marginalised communities.     

Likelihood Prediction for Generalized Linear Mixed Models under Covariate Uncertainty

This article presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction are explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. This article outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson errors-in-variable generalized linear model, it has been shown in certain cases that LP produces better results than already known methods.     

Ergonomic evaluation of postural stress in school workshop

The objective of this study is to compare the evaluation of postural analysis between a self-report questionnaire and physical assessments methods for students aged 13 to 15 years old in school workshop. 336 students were volunteered as participants to fill in the questionnaire and being observed in the workshop. Total of 104 positions were selected and analyzed while students performing their tasks. Questionnaire data was examined to specify the prevalence of postural stress symptoms. The relationship of postural stress by physical assessment methods (RULA and REBA methods) was defined to identify the risk level of students' working posture. From the results, comparison of four factors categorized from total of 22 questions among ages, the mean values were lower for 13 years old students meaning that they were faced higher posture problems while using the workstation. The obtained results from both physical assessment methods and questionnaire analysis have identified 13 years old students faced higher risk exposure. Analysis results emphasized the fact that self-reports questionnaire method has almost accurate as postural evaluation methods to identify physical risks in workplace. The result also shows that an intervention is needed to overcome the posture problems.