Learning organization and development of woman managers in Pakistan

Women's participation in economic activities in general and at managerial status in particular is insignificant in Pakistan. Furthermore, the opportunities for professional development of women managers are meagre because of multiple socio-cultural limitations. This paper attempts to draw a profile of female managers focusing, inter alia, on the trend and structure of women's human resource, ratio of employment, work environment and scope of development, efficiency at work, satisfaction level, professional commitment and forces inhibiting women access to jobs under the learning organization perspectives. It also exhibits issues bearing policy implications in regard to the development of women as managers and also as human resource.     

Joint modeling of longitudinal continuous,longitudinal ordinal,and time-to-event outcomes

Lifetime Data Analysis - In this paper, we propose an innovative method for jointly analyzing survival data and longitudinally measured continuous and ordinal data. We use a random effects...     

Construction of repeated measurements designs strongly balanced for residual effects

Abstract

Repeated Measurements Designs have been widely used in agriculture, animal husbandry, education, biology, botany and engineering. Balanced or strongly balanced repeated measurements designs are useful to balance out the residual effects. In this article, some new generators and construction procedures are proposed to obtain circular strongly balanced repeated measurements designs in periods of (a) equal sizes, (b) two different sizes, and (c) three different sizes.     

Quality of Life and Well-Being Ranking of Selected Districts of Khyber Pakhtunkhwa,Pakistan

Quality of life (QoL) is a multidimensional concept encompassing many aspects of an individual’s existence. It is not just a measure of material resources but of intangible environments which affect quality of life. The study concentrates on the province of Khyber Pakhtunkhwa, Pakistan, and looks at the QoL and well-being in thirteen districts representing the province’s major population. It followed an integrative approach to measuring quality of life. Principal component analysis was used to tackle with multidimensionality. Weighted factor scores were used as an index for ranking QoL and well-being on the basis of social indicators chosen in different life domains. The results show that districts having high urban disposition top the ranks in QoL in Khyber Pakhtunkhwa, like Peshawar, Mardan, Swat and Charsadda, while Bannu, Kohat and Lower Dir fall amongst the bottom districts in terms of QoL. The rural/urban ranking also follows similar patterns with a few exceptions.     

人类欲望与全球资本主义:挑战与机遇

东西方古代和现代对人性和人类欲望的哲学见解,为对国际全球资本主义狂潮以及其相关行业的必要性提供了思想资源。所有这些可以追溯到早期家庭幼儿教育,即亚里斯多德所说的"人类先验"以及张载所说的"美好生活",对人类欲望从结构上进行正确引导。在这方面,对于"模仿"和"欲望"这两个范畴以及其各自关系的深刻哲学反思,无论是预设还是被预设,都有助于重建此结构,而此结构可以产生这样的引导。     

An empirical bayes estimate of multinomial probabilities

This paper deals with the prblem of estimating simultaneously the parameters (Cell probabilities) of m ≤ 2 independent multinomial distributions, with respect to a quadratic loss functions. An empirical Bayes estimator is proposed which is shown to have smaller risk than the maximum likelihood estimator for sufficiently large values of mq, where q is a measure of the average diversity of the given multinomial populations. Some numerical results are given on the performance of the proposed estimator.     

Prediction of mechanical property of steel strips using multivariate adaptive regression splines

In recent times, the problem of prediction of properties of a steel strip has attracted enormous attention from different communities such as statistics, data mining, soft computing, and engineering. This is due to the prospective benefits of reduction in testing and inventory cost, increase in yield, and improvement in delivery compliance. The complexity of the problem arises due to its dependency on the chemical composition of the steel, and a number of processing parameters. To predict the mechanical properties of the strip (yield strength, ultimate tensile strength, and Elongation), a model based on multivariate adaptive regression spline has been developed. It is found that the prediction agrees well with the actual measured data.     

M-estimators of some GARCH-type models; computation and application

In this paper, we consider robust M-estimation of time series models with both symmetric and asymmetric forms of heteroscedasticity related to the GARCH and GJR models. The class of estimators includes least absolute deviation (LAD), Huber’s, Cauchy and B-estimator as well as the well-known quasi maximum likelihood estimator (QMLE). Extensive simulations are used to check the relative performance of these estimators in both models and the weighted resampling methods are used to approximate the sampling distribution of M-estimators. Our study indicates that there are estimators that can perform better than QMLE and even outperform robust estimator such as LAD when the error distribution is heavy-tailed. These estimators are also applied to real data sets.     

The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*

An auditor gives a going concern uncertainty opinion when the client company is at risk of failure or exhibits other signs of distress that threaten its ability to continue as a going concern. The decision to issue a going concern opinion is an unstructured task that requires the use of the auditor's judgment. In cases where judgment is required, the auditor may benefit from the use of statistical analysis or other forms of decision models to support the final decision. This study uses the generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model to predict which firms would receive audit reports reflecting a going concern uncertainty modification. The GRG2 optimizer has previously been used as a more efficient optimizer for solving business problems. The neural network model formulated using GRG2 has the highest prediction accuracy of 95 percent. It performs best when tested with a small number of variables on a group of data sets, each containing 70 observations. While the logit procedure fails to converge when using our eight variable model, the GRG2 based neural network analysis provides consistent results using either eight or four variable models. The GRG2 based neural network is proposed as a robust alternative model for auditors to support their assessment of going concern uncertainty affecting the client company.     

Spatial smoothing of low birth weight rate in Bangladesh using Bayesian hierarchical model

The term low birth weight refers an event where a newborn baby has a weight that is less than 2500?g. This is an essential indicator while the interest is in public health issues such as infant mortality, maternal complications, and antenatal care, etc. of a country, particularly, for a developing country like Bangladesh. The regional development programs are in the current priority list of Bangladesh government and other policy makers. Many of such regional development programs may need the spatial distribution of relative risk for low birth weight that can be obtained by mapping the risks over small area domains like the districts of Bangladesh. This study aims to find whether is there any spatial dependence among the relative risks of low birth weight for the districts of Bangladesh. This has been investigated using Moran's I statistic and a significant spatial dependence in the relative risks was found. Then, attempt has been made to rediscover the spatial distribution based on the idea of spatial smoothing. A Bayesian hierarchical model is used considering percent received antenatal care and female labor force participation as covariates to smooth the observed relative risks of low birth weight in 64 districts of Bangladesh. Revised spatial distribution taking the spatial dependence under consideration through intrinsic conditional autoregressive model is derived and showed in choropleth map along with its different behaviors.