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On Estimating the Variance of a Normal Distribution With Known Coefficient of Variation
Ray, S.K.,Sahai, A. The Korean Statistical Society 1978 Journal of the Korean Statistical Society Vol.7 No.2
This note deals with the estimations of the variance of a normal distribution $N(\theta,c\theta^2)$ where c, the square of coefficient of variation is assumed to be known. This amounts to the estimation of $\theta^2$. The minimum variance estimator among all unbiased estimators linear in $\bar{x}^2$ and $s^2$ where $\bar{x}$ and $s^2$ are the sample mean and variance, respectively, and the minimum risk estimator in the class of all estimators linear in $\bar{x}^2$ and $s^2$ are obtained. It is shown that the suggested estimators are BAN.
Changing Characteristics of Droughts over Kerala, India: Inter-Annual Variability and Trend
Abhilash S.,E. K. Krishnakumar,P. Vijaykumar,A. K. Sahai,B. Chakrapani,Girish Gopinath 한국기상학회 2019 Asia-Pacific Journal of Atmospheric Sciences Vol.55 No.1
Realized changes in the climate over Kerala received more attention during recent times under the back to back drought conditions prevailing over the state. The year 2016 registered as one of the worst and extreme drought year over Kerala in recent past. This extreme drought condition may be attributed to the combined effect of realized changes in the mean climate state as well as the climate variability.Both the recent and historic drought events over Kerala is examined and its possible impacts on different sectors like agriculture and water resource are studied using the standardized precipitation index (SPI). Historical occurrence of both the short term and long term water stress associated with deficit rainfall during monsoon and postmonsoon season is presented in the paper. It is found that south west monsoon rainfall over Kerala is decreasing over south Kerala during recent decades, whereas the post-monsoon rainfall is found to be increasing especially over south Kerala. There exists a weak relationship between Pacific SSTand Kerala rainfall. Trend analysis of SPI on different time scale showed negative trend and that negative trend increases with increasing time scale.