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In this paper, we consider the problem of estimating common location parameter of two exponential populations using type-II censored samples when the scale parameters are unknown. The loss function is taken as the quadratic loss. First, we derive a class of affine equivariant estimators, which includes the maximum likelihood estimator (MLE) and the uniformly minimum variance unbiased estimator (UMVUE). A sufficient condition for improving estimators in the class is derived. Consequently, estimators dominating MLE and UMVUE in terms of risk values are obtained. An example is given to compute the estimates using our result. Finally a simulation study has been carried out to numerically compare the risk functions of all the estimators.

Introduction Suicide is a major social and health issue in India. Yearly statistics show a concerning increasing pattern of suicidal deaths in India which is higher in comparison to the global trend. There is limited evidence regarding historical analysis of suicide or any forecasting for suicide in India towards predicting the possible risks of death due to suicide. Methods This paper examines the trend of suicide rate and characteristics of suicide victims in India, based on the longitudinal time series data over the last 50 years—collected from the National Crime Record Bureau Reports (1969 to 2018) of the Government of India. In our analysis, we have used the time series model to forecast the suicide rates in India for the next decade. ARIMA (4,1,0) model is found to be the best fit model for forecasting the data. Findings There has been an observable and rising trend of suicide rates in India over the last five decades. The forecast indicates a continuance of rising suicide cases for an upcoming couple of years in India with a limited decline in the following years. The prediction model indicates a future relatively consistent pattern of suicide in India which does not seem to be a very encouraging trend. As we have not included the period staring the year 2020 onwards affected by Covid-19 and which has several disruptions in personal and family spaces, the projected suicide trend during the period of next two to three years (2020–22) may rise far high and then it may show a declining path. Along with this, there is a shift in means of suicide in the last couple of decades. Constituting the second-highest number of cases, Illness associated suicide was visibly a serious concern. Conclusion The present analysis finds that there is no visible substantial relief for suicide deaths during the coming years in India. On the other hand, more extensive exploration of sample cases may provide important information for suicide prevention. Availability of detailed and more inclusive data will be highly useful for analysis and suicide preventive policies. Investment in public health care and other welfare activities like education and employment generation will yield visible positive results in suicide control.

Social networking sites (SNSs) are used to interact with friends and stay connected. The SNSs are increasingly being used by employers as a source of background checks on employees, including the prospective candidates for employment. Employers are making decisions on the basis of information posted on SNSs. The decisions regarding selection, retention or exit are in part influenced by information posted on such sites. The present study examines the perceptions of current employees on the information checks done by employers using networking sites like Facebook. The current study also provides insights that can be followed by both the employees and employers related to usages of SNSs.

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PM 2.5 (particulate matter size less than 2.5 µm, also called Respirable suspended particulate matter (RSPM)) is causing devastating effects on various living entities and is deleterious more than any other pollutants. As ambient air pollution is a scourge to India, in the present research work, PM 2.5 is considered and the current study aims to estimate surface level PM 2.5 concentrations using satellite-derived aerosol optical depth (AOD) along with meteorological data obtained from reanalysis and in-situ measurements over two different cities of India, namely: Agra, a non-industrial site for a study period of 2011-2015 and Rourkela, a highly industrialized location for 2009-2013, respectively. From the average daily variation of PM 2.5 , the pollution levels are critical and exceeding the threshold values defined by the pollution control board for most of the days at both the sites. Satellite-observed AOD values were also found to be very high over Agra (average AOD 0.76-0.8) and Rourkela (average AOD 0.4-0.46) during the study period. The annual exceedance factor (AEF) values over Agra and Rourkela were found to be always > 1.5 which indicates the above critical state of pollution. Traditional simple linear regression method (Model I), multiple linear regression (Model II (a-e)), log-linear regression (Model III) and conditional based MLR (Model IV and Model V) methods are applied to estimate the PM 2.5 concentrations over Taj for Agra region for a study period of 2011-2015 and Sonaparbat for Rourkela region for a study period of 2009-2013. The models obtained over Taj and Sonaparbat are applied to Rambagh (2011Rambagh ( -2015 and Rourkela (2009-2013) sites for validation. The coefficient of determination (R) between observed and estimated values are found to be statistically significant for model II (e) during training and validation at both the sites and model performance is adequate. The Model II (e) can thus be used as a unified explanatory model for the estimation of PM 2.5 over these two monitoring stations.

T.V. Rao and Charu Sharma, 100 Managers in Action. New Delhi: Tata McGraw-Hill Education Private Limited, 2012, xv + 392 pp., ₹ 475 [Paperback].

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