Nonparametric control charts based on runs and Wilcoxon-type rank-sum statistics

In this article, we introduce three new distribution-free Shewhart-type control charts that exploit run and Wilcoxon-type rank-sum statistics to detect possible shifts of a monitored process. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of these charts is that, due to their nonparametric nature, the false alarm rate (FAR) and in-control run length distribution is the same for all continuous process distributions. Tables are provided for the implementation of the charts for some typical FAR values. Furthermore, a numerical study carried out reveals that the new charts are quite flexible and efficient in detecting shifts to Lehmann-type out-of-control situations.     

Covariance-regularized regression and classification for high dimensional problems

Summary.  We propose covariance-regularized regression, a family of methods for prediction in high dimensional settings that uses a shrunken estimate of the inverse covariance matrix of the features to achieve superior prediction. An estimate of the inverse covariance matrix is obtained by maximizing the log-likelihood of the data, under a multivariate normal model, subject to a penalty; it is then used to estimate coefficients for the regression of the response onto the features. We show that ridge regression, the lasso and the elastic net are special cases of covariance-regularized regression, and we demonstrate that certain previously unexplored forms of covariance-regularized regression can outperform existing methods in a range of situations. The covariance-regularized regression framework is extended to generalized linear models and linear discriminant analysis, and is used to analyse gene expression data sets with multiple class and survival outcomes.     

SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELS

Semiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more naturally handled within the graphical model architecture. Directed acyclic graphs, also known as Bayesian networks, play a prominent role. Graphical model-based Bayesian 'inference engines', such as bugs and vibes , facilitate fitting and inference. Underlying these are Markov chain Monte Carlo schemes and recent developments in variational approximation theory and methodology.     

VARIATIONAL BAYESIAN ANALYSIS FOR HIDDEN MARKOV MODELS

The variational approach to Bayesian inference enables simultaneous estimation of model parameters and model complexity. An interesting feature of this approach is that it also leads to an automatic choice of model complexity. Empirical results from the analysis of hidden Markov models with Gaussian observation densities illustrate this. If the variational algorithm is initialized with a large number of hidden states, redundant states are eliminated as the method converges to a solution, thereby leading to a selection of the number of hidden states. In addition, through the use of a variational approximation, the deviance information criterion for Bayesian model selection can be extended to the hidden Markov model framework. Calculation of the deviance information criterion provides a further tool for model selection, which can be used in conjunction with the variational approach.     

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model. The authors would like to thank the editor and referees for their helpful comments. This work was supported by CNPq, Brazil.     

Social Harmony in Hong Kong: Level,Determinants and Policy Implications

This study aims at ascertaining how Hong Kong people perceive Hong Kong as a harmonious society. It also identifies the elements that are most conducive to social harmony in Hong Kong, so that the government could take reference when formulating new policies. 1,062 adults residents were asked to rate their perceived level of social harmony and their satisfaction with 36 items (divided into three dimensions: public governance, society, and economy, family and work) for which the research team believes would be influencing the perceived level of social harmony. Results show that the average rating of social harmony was 5.57 (out of 10), delineating a moderate level of social harmony. Subsequent multivariate factor analysis and regression analysis show that the four extracted factors (from the three dimensions) had significant impacts on the level of social harmony. These were, in order of significance: (a) public governance, (b) social solidarity and respect, (c) economy/family/work and, (d) social tolerance and progressiveness. According to the factor loadings of each significant factor, we identified four core values which we hope the government would consider when formulating new policies, as follows: (1) A Justice Government with Sincerity on Communication, (2) Mutual Support and Respect with Integrity and Dedication, (3) Dedication to One’s Job and Community by Helping the Needed and, (4) Creativity and Progressiveness with Tolerance. Implications for policy making are discussed. The study was conducted under the direction and guidance of the Fostering Social Harmony Task Force of the Hong Kong Professionals and Senior Executives Association (HKPASEA). The authors acknowledge the kind support and assistance provided by the Council Members of HKPASEA and staff members of the Centre for Corporate Governance and Financial Policy at Hong Kong Baptist University. We are also grateful to Prof. Alex Michalos and Prof. P. K. Ip for their comments and suggestions given at the International Conference on National Well-Being held in November 2006 at the National Central University, Taiwan.     

Quality_Family Deployment: A New Perspective in Determining Priority Importance for Improving Work Performance in Organization

Determining priority importance is a matter of concerns among the organization to improve their performance. One of the important aspects that should be considered by the organization is management of human resources, comprising of members who have their own family life. In this paper, we deliver a new perspective for organization to provide priority importance for their members with respect to family matters in order to inculcate the sense of belonging in the organization. To be effective in considering family matters in the organizational policy making, closer look of family characteristics are required. The idea of translating several family characteristics as quality variables and applying the quality function deployment (QFD) method to these variables could present a new way of improving the decision making in the organization by considering the process of decision in the family. Quality function deployment for family (QFDF) produces a friendly interpretation of a highly complex and intangible matters around family life; thus, making the assessment of a family easier. QFD is applied on the data gathered from a questionnaire survey based on 1,213 families in West Malaysia, Malaysia. Twelve variables are identified as voice of family, where seven of them are found to have the highest priority of importance. These variables could also be translated into quality variables in the context of organization, the strategy of improvement for the family could be interpreted as strategy for improvement in the organization. Furthermore, the results of this study provide suggestion to improve actions for managing human resource. In the discussion, three most high ranked variables from both perspectives of family and organization are considered.     

A New Malaysian Quality of Life Index Based on Fuzzy Sets and Hierarchical Needs

The Malaysian Quality of Life Index (MQLI) released by the Economic Planning Unit (EPU), has led authors to search for alternative method of expressing this index. One of the limitations in MQLI computations is the failure to recognise unequal weights for each accounted component. This paper offers a new way of expressing the quality of life index using a mathematical modelling based on fuzzy sets theory and the proposed weights based on Maslow’s theory of hierarchical human needs. The indices of 11 components that were used to compute MQLI, again be gathered as a basis in expressing a new Malaysian Fuzzy Quality of Life Index (MFQLI). The new indices for each component yielded through a normalisation process prior weighting and aggregation to compose a new MFQLI. It was found that a fuzzy sets approach with the inclusion of weights based on human needs yielded a better index of quality of life than the MQLI.     

Determinants of business success: an examination of Asian-owned businesses in the USA

Using confidential microdata from the US Census Bureau, we investigate the performance of Asian-owned businesses. Using regression estimates and a special non-linear decomposition technique, we explore the role that class resources, such as financial capital and human capital, play in contributing to the relative success of Asian businesses. We find that Asian-owned businesses are more successful than white-owned businesses for two main reasons—Asian owners have high levels of human capital and their businesses have substantial start-up capital. Using detailed information on both the owner and the firm, we estimate the explanatory power of several additional factors.

Children's Experiences of Time When a Parent Travels for Work

This qualitative study focuses on the different ways time is experienced by children in families who face time challenges because of a family member's job that required work travel. Data are from a family‐level study that includes interviews of all family members older than age 7. Using grounded theory methodology, this study illustrates the ways in which job demands and family processes interact. The analysis centers on 75 children's perspectives from 43 families. Holding together assessments of having enough time while wanting more time with their parents, children express emotion, generally unrecognized by parents, around the topic of family time. Children's experience of time with parents is rushed or calm, depending on the activities done in time and the gender of the parent with whom they spend time. Findings are interpreted through a feminist social constructionist lens.