{"title":"ESTIMATION OF POPULATION VARIANCE IN LOG – PRODUCT TYPE ESTIMATORS UNDER DOUBLE SAMPLING SCHEME","authors":"Prabhakar Mishra, Rajesh Singh, S. Khare","doi":"10.13052/jrss2229-5666.1222","DOIUrl":"https://doi.org/10.13052/jrss2229-5666.1222","url":null,"abstract":"It is experienced that auxiliary information when suitably incorporated yields more efficient and precise estimates. Mishra et al. (2017) have introduced a log type estimator for estimating unknown population mean using ancillary information in simple random sampling. Here we propose an improved log-product type estimator for population variance under double sampling. Properties of the estimators are studied both mathematically and numerically. \u0000 ","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2019-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44390455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FORECASTING OF AREA AND PRODUCTION OF CASHEW NUT IN DAKSHINA KANNADA USING ARIMA AND EXPONENTIAL SMOOTHING MODELS","authors":"M. Chaithra, Pramit Pandit, Bishvajit Bakshi","doi":"10.13052/jrss2229-5666.1226","DOIUrl":"https://doi.org/10.13052/jrss2229-5666.1226","url":null,"abstract":"The cultivation and marketing of cashew nut involve a considerable amount of work force. Hence, it plays a vital role in the Indian economic scenario. In this context, an attempt has been made to forecast the area and production of cashew nut with a view to help the planners in recommending policies regarding cashew nut. Due to autocorrelation in the data, time series forecasting models such as ARIMA and exponential smoothing models were adopted. Detection and removal of 3 significant outliers, i.e. 1 for area under cashew nut and 2 in case of cashew nut production, were done before fitting the models. Holt’s model was found to have better forecasting ability with lowest RMSE value (1386.13) among the different models fitted for forecasting the area under cashew nut. From this model, area (ha) under cashew nut was forecasted to be 34492.10, 34974.81 and 35474.87 for the year 2018, 2019 and 2020, respectively. In case of cashew nut production, Brown’s linear trend model, with RMSE value (10020.19), was observed to have better forecasting ability among the tried models. Production of cashew nut (in tonnes) was forecasted to be 10230.20, 10996.81 and 11833.00 for the year 2018, 2019 and 2020, respectively. \u0000 ","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49054471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"REGRESSION-IN-RATIO ESTIMATORS IN THE PRESENCE OF OUTLIERS BASED ON REDESCENDINGM-ESTIMATOR","authors":"Aamir Raza, Muhmmad Noor-ul-Amin, M. Hanif","doi":"10.13052/jrss2229-5666.1221","DOIUrl":"https://doi.org/10.13052/jrss2229-5666.1221","url":null,"abstract":"In this paper, a robust redescending M-estimator is used to construct the regression-inratio estimators to estimate population when data contain outliers. The expression of mean square error of proposed estimators is derived using Taylor series approximation up to order one. Extensive simulation study is conducted for the comparison between the proposed and existing class of ratio estimators. It is revealed form the results that proposed regression-in-ratio estimators have high relative efficiency (R.E) as compared to previously developed estimators. Practical examples are also cited to validate the performance of proposed estimators. \u0000 ","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42818386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}