Tests of Covariance Matrices for High Dimensional Multivariate Data Under Non Normality

Ahmad and von Rosen (2014 Ahmad, M. R. (2014). A U-statistic approach for a high-dimensional two-sample mean testing problem under non-normality and Behrens-Fisher setting. Annals of the Institute of Statistical Mathematics 66:33–61.[Crossref], [Web of Science ®] , [Google Scholar]) presented test statistics for sphericity and identity of the covariance matrix of a multivariate normal distribution when the dimension, p, exceeds the sample size, n. In this note, we show that their statistics are robust to normality assumption, when normality is replaced with certain mild assumptions on the traces of the covariance matrix. Under such assumptions, the test statistics are shown to follow the same asymptotic normal distribution as under normality for large p, also when p > >n. The asymptotic normality is proved using the theory of U-statistics, and is based on very general conditions, particularly avoiding any relationship between n and p.     

Goodness-of-fit testing of a weak memoryless property of life distributions

A life distribution is said to have a weak memoryless property if its conditional probability of survival beyond a fixed time point is equal to its (unconditional) survival probability at that point. Goodness‐of‐fit testing of this notion is proposed in the current investigation, both when the fixed time point is known and when it is unknown but estimable from the data. The limiting behaviour of the proposed test statistic is obtained and the null variance is explicitly given. The empirical power of the test is evaluated for a commonly known alternative using Monte Carlo methods, showing that the test performs well. The case when the fixed time point t₀ equals a quantile of the distribution F gives a distribution‐free test procedure. The procedure works even if t₀ is unknown but is estimable.     

The plight of rural women: alternatives for action

Women in rural areas perform many of the agricultural tasks as well as the household care tasks. In addition to food production, looking after children, and cultivating cash crops, women also process food, carry water, make cloth, and work 15-16 hours, often much longer than the men. Too often development programs disregard the needs of women altogether. Modernization has often had a negative effect on women. They have no access to modern tools or credit. Land reform, land settlement programs, and cooperatives have neglected to consider women's interests, roles, and position. Technogical progress has resulted in creating new inequalities between rural men and women. Development has increased the workload of women who are unpaid family helpers, and time-saving mechanised device have replaced women's jobs. In most developing countries women are active in home-based industrial production. The contractor who provides the material and collects the finished product is often a wealthy landowner who also get the profits. Technical cooperation projects should be geared more directly to food processing and traditional sectors where women predominate with the goal of reducing work loads. Organization or group action is necessary to achieve economies of scale; to eliminate middle men, money-lenders and traders profiting from women's work; and, to provide solidarity and support to women otherwise isolated in their homes and on their farms.     

Robustness of subset response surface designs to missing observations

Experiments designed to investigate the effect of several factors on a process have wide application in modern industrial and scientific research. Response surface designs allow the researcher to model the effects of the input variables on the response of the process. Missing observations can make the results of a response surface experiment quite misleading, especially in the case of one-off experiments or high cost experiments. Designs robust to missing observations can attract the user since they are comparatively more reliable. Subset designs are studied for their robustness to missing observations in different experimental regions. The robustness of subset designs is also improved for multiple levels by using the minimax loss criterion.     

Mediation outcomes and sources of impasse: An empirical investigation

This study examines two of the four determinants of mediation effectiveness identified in Kochan and Jick’s (1978) model of the public sector mediation process: source of impact and situational factors. Questionnaire data were directly obtained from 240 Bangladesh management and union officials. Discriminant analysis identified several sources of impasse for both union and management groups, but no situational factors were found to accurately predict case settlement. Results are discussed in terms of U.S. public sector mediation research.     

Forecasting demand for food in Libya—using confidence limits

Many developing countries are not self-sufficient in food production and they depend on food imports. In order to plan imports well in advance, the demand for food must be forecasted. If the forecasts are too low, the people suffer. On the other hand if the forecasts are too high—the food being a perishable commodity—resources of the country are wasted. The Food and Agricultural Organization of the United Nations (FAO) undertakes such forecasts occasionally. The FAO however links the food consumption to the income of a country and then just assume future income. Such forecasts have no scientific validity and could both fall short or be grossly excessive. In this study, the methodologies of Time Series and Regression Analysis are combined to avoid any guesses. Then confidence intervals are built so that it can be stated, e.g. with 95 per cent confidence that a nation will not eat more than the amount specified. A comparison of costs is made and it is shown that a country can save millions of dollars through the method of statistical confidence limits rather than by adding arbitrary quantities to means and averages. Finally savings possible in some other developing countries, by adopting the proposed method, are tabulated.     

Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing

Research in assembly optimisation is presently inclined towards integrative measures. Several benefits of simultaneously optimised Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) have been highlighted by researchers to have better solution quality, shorter time-to-market, and minimalised error during planning. Recently, several efforts have been made to realise integrated assembly optimisation. However, none of the published research considered the two-sided assembly line problem. This paper presents an integrated ASP and ALB optimisation in a two-sided assembly environment (2S-ASPLB), which is mainly adopted in automotive assembly process. In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. The computational experiments were conducted in a few stages, beginning with the identification of the best decoding approach for 2S-ASPLB. Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. The results indicated that the priority factor (PF) decoding approach had better performance compared with others. Meanwhile, in comparison with well-established algorithms, MOMVO performed better in convergence and solution distribution. The case study results indicated the applicability of proposed 2S-ASPLB model and algorithm to improve line efficiency in assembly line. The main contribution of the research is a new 2S-ASPLB model and optimisation scheme, which can assist manufacturer in designing better assembly layout.