{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/32612"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/32612","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"Time series analysis of RTC Great Lakes recruit graduate data","abstract":"This thesis formulates predictions for Recruit Training Command (RTC) Great Lakes' recruit graduation rates based on two econometric approaches. The Navy's recruit graduation rates exhibit pronounced seasonal and long-term behaviors, which tends to cause logistical problems at RTC. The modeling and subsequent forecast of RTC graduation rates is therefore an important management tool which could facilitate future planning for both RTC Great Lakes and the U. S. Navy. First the multiplicative decomposition method is employed to produce a model. As an alternative the autoregressive integrated moving average (ARIMA) process is used to describe the data. In both instances, satisfactory forecasting results are attained.","abstract_html":"This thesis formulates predictions for Recruit Training Command (RTC) Great Lakes' recruit graduation rates based on two econometric approaches. The Navy's recruit graduation rates exhibit pronounced seasonal and long-term behaviors, which tends to cause logistical problems at RTC. The modeling and subsequent forecast of RTC graduation rates is therefore an important management tool which could facilitate future planning for both RTC Great Lakes and the U. S. Navy. First the multiplicative decomposition method is employed to produce a model. As an alternative the autoregressive integrated moving average (ARIMA) process is used to describe the data. In both instances, satisfactory forecasting results are attained.","abstract_has_math":false,"creators":["Bosque, Edward F."],"institution":"Monterey, California. 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First the multiplicative decomposition method is employed to produce a model. As an alternative the autoregressive integrated moving average (ARIMA) process is used to describe the data. In both instances, satisfactory forecasting results are attained."]},{"key":"dc:title","label":"Title","values":["Time series analysis of RTC Great Lakes recruit graduate data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Euske, Kenneth J."],"dc:contributor.department":["Management"],"dc:creator":["Bosque, Edward F."],"dc:date.accessioned":["2013-05-06T18:43:16Z"],"dc:date.available":["2013-05-06T18:43:16Z"],"dc:date.issued":["1998-12"],"dc:description.abstract":["This thesis formulates predictions for Recruit Training Command (RTC) Great Lakes' recruit graduation rates based on two econometric approaches. The Navy's recruit graduation rates exhibit pronounced seasonal and long-term behaviors, which tends to cause logistical problems at RTC. 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