A rank test for stochastically ordered alternatives

A rank test based on the number of ‘near-matches’ among within-block rankings is proposed for stochastically ordered alternatives in a randomized block design with t treatments and b blocks. The asymptotic relative efficiency of this test with respect to the Page test is computed as number of blocks increases to infinity. A sequential analog of the above test procedure is also considered. A repeated significance test procedure is developed and average sample number is computed asymptotically under the null hypothesis as well as under a sequence of contiguous alternatives.     

Sequential estimation of the mean of a first-order autoregressive process

This paper considers the problem of sequential point estimation, under an appropriate loss function, of the location parameter when the errors form an autoregressive process with unknown scale and autoregressive parameters, A sequential procedure is developed and an asymptotic second order expansion is provided for the difference between expected stopping time and the optimal fixed sample size procedure. Also, the asymptotic normality of the stopping time is proved. Though the procedure Is asymptotically risk efficient, it. Is not clear whether it has bounded regret.     

A sequential scheme to estimate the optimal age replacement policy

Consider a system which is subject to failure and must be replaced when this occurs. If it costs less to replace the system in advance before failure, it may be advantageous to use an age replacement policy. However, the optimal age to replace the system is unknown if the underlying failure distribution is unknown. This paper develops a scheme to update the current estimate of the optimal age replacement policy in an on-line fashion and simultaneously controlling costs by reducing system failures.     

The Selection of Computer-Aided Software Engineering Tools: A Multi-Criteria Decision Making Approach

The selection of the appropriate computer-aided software engineering (CASE) tools to suit the needs of an organization requires the systematic application of the multi-criteria decision methodology (MCDM). In order to make a case for the use of MCDM, the application of the ELECTRE I method to the selection of CASE tools from a possible set of six alternatives is demonstrated. The demonstration helps in gaining a grasp of the MCDM approach and the ELECTRE I method. There is potential for the application of the MCDM approach in other software engineering decisions, especially in the feasibility analysis of the systems life cycle.     

Multistage Modeling of Lung Cancer Mortality Among Arsenic-Exposed Copper-Smelter Workers

Multistage modeling incorporating a time-dependent exposure pattern is applied to lung cancer mortality data obtained from a cohort of 2802 arsenic-exposed copper-smelter workers who worked 1 or more years during the period 1940-1964 at a copper smelter at Tacoma, Washington. The workers were followed for death through 1976. There were 100 deaths due to lung cancer during the follow-up period. Exposures to air arsenic levels measured in micrograms/m3 were estimated from departmental air arsenic and workers urinary arsenic measurements. Relationships of different temporal variables with excess death rates are examined to judge qualitatively the implications of the multistage cancer process. Analysis to date indicates a late stage effect of arsenic although an additional early stage effect cannot be ruled out.     

Socio-demographic Correlates of Subjective Well-being in Urban India

This study aimed to explore subjective well-being (SWB) in an urban Indian sample. Adults (n = 1099) belonging to two wards in the city of Bangalore in South India, responded to a study-specific questionnaire. This paper is based on data generated as part of an ongoing larger study looking at correlates of SWB. Almost equal number of men and women responded to the study and their age ranged from 20 to 81 years (mean age 37 years). Majority of them were married, Hindus, from middle socio-economic status, had studied above pre-university level and more than half were earning. The mean scores on positive affect (40.9), negative affect (27.6) and life satisfaction (24) suggested above average levels of SWB. Higher age, being married, having higher education, higher income and working in a full time job seemed to improve life satisfaction and decrease negative affect. Religion was also significantly associated with negative affect. Step-wise regression analysis suggested that only education and income were important predictors of positive affect, while negative affect was better predicted by age, income, work status and religion. Life satisfaction was predicted by income, age and education. The important correlates of SWB for men and women were somewhat different. Overall, sociodemographic variables have minimal effect on SWB in urban India and research needs to explore other predictors of SWB.     

Tests for exponentiality

The idea of measuring the departure of data bu a plot of obeserved observations against their expectation has been expeetations has been exploited in this paper to develop tests for exponentiality the tests are for parameter two parameter exponential distribution with complete sample and one parameter exponential distribution with complete sample and one large sample distributions of the test statistics critical points have been computed for different levels of significance and applications of these have been computed for differents levels of significance and applications of these tests have been discussed in case of three data sets.     

Worlds apart or a part of the world? Public relations issues and challenges in India

This study examines modern public relations in India investigating current issues, trends and leadership in communication management. Using a survey of Indian practitioners, it compares public relations in India with global trends. Findings suggest that practice in India is interdependent and changing dynamically with global influences, though a global–local dialectic is clearly present. Country-level differences are evident with development of human capital seen as the top issue in the region. At the same time, similar to other countries, the industry in India is also dealing with issues of digitization and information flow, struggling with measurement concerns, and trying to stay on top of crisis management preparedness.     

Bayesian Methods for Model Uncertainty Analysis with Application to Future Sea Level Rise

This paper addresses the use of data for identifying and characterizing uncertainties in model parameters and predictions. The Bayesian Monte Carlo method is formally presented and elaborated, and applied to the analysis of the uncertainty in a predictive model for global mean sea level change. The method uses observations of output variables, made with an assumed error structure, to determine a posterior distribution of model outputs. This is used to derive a posterior distribution for the model parameters. Results demonstrate the resolution of the uncertainty that is obtained as a result of the Bayesian analysis and also indicate the key contributors to the uncertainty in the sea level rise model. While the technique is illustrated with a simple, preliminary model, the analysis provides an iterative framework for model refinement. The methodology developed in this paper provides a mechanism for the incorporation of ongoing data collection and research in decision-making for problems involving uncertain environmental change.