{"title":"Joint Modeling of Mixed Responses with Bayesian Modeling and Neural Networks: Performance Comparison with Application to Poultry Data","authors":"J. C. Hapugoda, M. Sooriyarachchi","doi":"10.4038/sljastats.v19i2.8019","DOIUrl":"https://doi.org/10.4038/sljastats.v19i2.8019","url":null,"abstract":"Joint modeling of mixed responses has become a popular research area due to its applicability in many disciplines. The interest of this study is joint modeling of survival and count data. Survival data is continuous in nature with censoring information combined to it, while count is a discrete variable. Due to this fact, joint modeling of these two variables will be a challenging task, but it will provide interesting and improved results than modeling these two variables separately. In this study, the concept of joint modeling of survival and count data has been carried out using two approaches: Bayesian modeling and Neural Networks, in order to compare their performances. The results of an application to the poultry data revealed that the Neural Network has a better fit in general.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41710297","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":"Efficiency of Neighbouring Designs for First Order Correlated Models","authors":"R. S. Kumar","doi":"10.4038/sljastats.v19i2.8020","DOIUrl":"https://doi.org/10.4038/sljastats.v19i2.8020","url":null,"abstract":"The comparison of efficiency of Complete and Incomplete Nearest Neighbour Balanced Block Designs over regular block design using average variance, generalized variance and min-max variance with the error term e given in the NNBD model follows using first order correlated models. It is observed that, RH and RD show increasing efficiency values for direct and neighbour effects (left and right) for MA(1) models. The RA and RG show neither increasing nor decreasing efficiency values are observed for direct and neighbouring effects for AR(1) and MA(1) models. In the case of ARMA(1,1) model, neither increasing nor decreasing efficiency values have been observed for average variance and generalized variance. The RE shows decreasing efficiency values with p in the interval 0.1 to 0.4 for direct and neighbouring effects for AR(1), MA(1) and ARMA(1,1) models.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43476510","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":"Application of Quick Switching System-1 with Single sampling Plan as reference plan through Minimum Sum of Risks in Determining Economic Ordering Policies under Permissible Delay in Payments","authors":"K. Veerakumari, H. Aruna","doi":"10.4038/sljastats.v19i2.7980","DOIUrl":"https://doi.org/10.4038/sljastats.v19i2.7980","url":null,"abstract":"Conventionally, all Economic Ordering model tacitly assumes that the immediate payment with the shipment of the products. But, in practice, the vendor may allow permissible delay in payments to the buyer. Quality management with minimized cost is the crucial factor for organization’s growth. Inspecting 100% of the products are time-consuming and costly especially when it involves destructive testing or inspection cost is huge. Acceptance sampling plan by attributes provides an effective solution to minimize the cost and consumes less time. Quick Switching System-1with two intensity of inspection is ease to apply as it enables instantaneous switch between normal and tightened inspection depends on the quality of the product. With more reliable products normal inspection is employed and vice versa.QSS-1 plan with minimum sum of risks carries another advantage of reducing the consumer and producer’s risk. With the application of the QSS-1 through minimum sum of risks on the EOQ model with permissible delay in payments buyer and vendor gets minimized cost, minimized risk and less time consuming process.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43124467","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}
K. S. Saubhagya, W. M. L. K. N. Wijesekara, I. T. Jayamanne, K. P. A. Ramanayake
{"title":"Airline Seats Allocation Optimization Through Revenue Management","authors":"K. S. Saubhagya, W. M. L. K. N. Wijesekara, I. T. Jayamanne, K. P. A. Ramanayake","doi":"10.4038/sljastats.v19i2.8021","DOIUrl":"https://doi.org/10.4038/sljastats.v19i2.8021","url":null,"abstract":"Revenue Management has recently gained a solid recognition in Airline industry. It acts as a strategic and tactic provider to manage the uncertainty in demand for their perishable products in the most profitable manner as possible. The Airline Revenue Management tries to attain an effective seat inventory control by utilizing the forecasts of future bookings, the revenue values related with each fare class, and the booking requests by the passengers which in turn will maximize the total revenue of a flight. This paper attempts to propose a novel approach in optimizing the seat inventory control by jointly utilizing the statistical forecasting together with revenue management. The revenue value associated with each point of sale (origin) has been considered when locating seats for a future departure instead of concerning the revenue values of each fare class. Further, it describes a method to obtain optimal seat protection levels that should be reserved from a lower fare origin for a higher fare origin and the nested structure of booking limits for each fare origin so as to optimize the seat allocation in a future departure. A novel approach using Functional Principal Component Regression (FPCR) was carried out to model and forecast the future demand and revenue value for each origin, using historical bookings and revenue values. The Expected Marginal Seat Revenue (EMSR) decision model was developed to address the uncertainty associated with this forecasted future demand and to gain the nested structure of booking limits. Finally, the forecasted booking limits were updated with actual booking requests prior to the flight departure. At the point of verification, it showed a remarkably maximized total revenue over the existing method. Thus, it is suggested that the optimal seat allocation for a better seat inventory control in airlines can be achieved by jointly utilizing the proposed FPCR and EMSR methods.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48368714","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":"Can We Ex Post Facto Justify Duckworth-Lewis Rule?","authors":"Kalyan Joshi, M. B. Rajarshi","doi":"10.4038/sljastats.v19i3.8046","DOIUrl":"https://doi.org/10.4038/sljastats.v19i3.8046","url":null,"abstract":"In a one-day international cricket match, due to disturbances such as rain or storm, at least one of teams cannot bat for stipulated fifty overs. The Duckworth-Lewis rule is then applied so that the match possibly ends up with a decision. We explore whether the rule can be justified based on statistical analysis of outcomes of oneday matches in which all the stipulated overs were bowled as well as matches in which it was needed to apply the rule. Our analysis shows that the rule is quite fair.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42814331","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":"Improved Estimation of Sensitive Mean Using Hybrid of Partial and Optional Scrambling in the Presence of Non-Sensitive Auxiliary Information","authors":"Z. Hussain, Waqas Arshad","doi":"10.4038/sljastats.v19i3.8045","DOIUrl":"https://doi.org/10.4038/sljastats.v19i3.8045","url":null,"abstract":"This article is about studying ratio, product and regression methods for estimating sensitive mean using a two-stage optional randomized response model by Gupta et al. (2010) and information on non-sensitive auxiliary variable. In particular, the additive randomized response model is used to further enhance the efficiency of the ratio, product and regression estimators (Gupta et al., 2010). We compare our proposed auxiliary information based two-stage optional randomized response estimator with recently proposed auxiliary information-based estimators. Through algebraic comparisons, it is shown that the proposed ratio, product and regression estimators are better than the corresponding estimators proposed in some recent studies. The results are also supported by a numerical study.","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42511836","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":"Modeling the Effect of Antipsychotic Drugs on Body Weight of Psychiatric Patients","authors":"S. A. Taiwo, Oladunni O. F. Ololade","doi":"10.4038/sljastats.v19i3.8044","DOIUrl":"https://doi.org/10.4038/sljastats.v19i3.8044","url":null,"abstract":"","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47339968","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":"The Use of Multiple Imputation for Data Subject to Limits of Detection.","authors":"Ofer Harel, Neil Perkins, Enrique F Schisterman","doi":"10.4038/sljastats.v5i4.7792","DOIUrl":"https://doi.org/10.4038/sljastats.v5i4.7792","url":null,"abstract":"<p><p>Missing data due to limit of detection and limit of quantification is a common obstacle in epidemiological and biomedical research. We are interested in methodologies that provide unbiased and efficient estimates of these missing data while using popular statistical software. We describe a multiple imputation (MI) procedure for cross-sectional and longitudinal data which examines the sources of variation of hormones levels throughout the menstrual cycle conditional on specific biomarkers. We describe the rational, procedure, advantages and disadvantages of the multiple imputation procedure. We also provide a comparison to commonly used missing data procedures (complete cases analysis and single imputation). We illustrate our approach using the BioCycle data where we are interested in the effects of Vitamin E and Beta-carotene on Progesterone levels. We also evaluate the longitudinal impact of changes in Vitamin E on Progesterone levels over time. Finaly, we demonstrate the advantages of using MI over complete case analysis or naive single replacement in both cross-sectional and longitudinal analysis where measurements below the limit of quantification (LOQ) are unreported. We also illustrate that if available, inclusion of potentially demined unreliable data below the limit of detection (LOD) improves simple estimation substantially.</p>","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":"5 4","pages":"227-246"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4838401/pdf/nihms752051.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34487518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A maximum Likelihood Approach to Analyzing Incomplete Longitudinal Data in Mammary Tumor Development Experiments with Mice.","authors":"Jihnhee Yu, Albert Vexler, Alan D Hutson","doi":"10.4038/sljastats.v13i0.5124","DOIUrl":"10.4038/sljastats.v13i0.5124","url":null,"abstract":"<p><p>Longitudinal mammary tumor development studies using mice as experimental units are affected by i) missing data towards the end of the study by natural death or euthanasia, and ii) the presence of censored data caused by the detection limits of instrumental sensitivity. To accommodate these characteristics, we investigate a test to carry out K-group comparisons based on maximum likelihood methodology. We derive a relevant likelihood ratio test based on general distributions, investigate its properties of based on theoretical propositions, and evaluate the performance of the test via a simulation study. We apply the results to data extracted from a study designed to investigate the development of breast cancer in mice.</p>","PeriodicalId":91408,"journal":{"name":"Sri Lankan journal of applied statistics","volume":"13 1","pages":"61-85"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70154210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}