Publications-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 Sequential Sampling in the Search for New Shared Species
作者 余清祥
Yue, Jack C. ; Clayton, Murray K.
貢獻者 統計系
關鍵詞 Optimal stopping; Comparing populations; Similarity index; Discovering new species; Simulation
日期 2012.05
上傳時間 24-Jun-2014 14:58:55 (UTC+8)
摘要 In microbial sciences, as well as other disciplines, it is often valuable to sample communities in a sequential or group sequential manner, in order to determine their structure or their similarity. We develop sequential sampling procedures to accomplish this by first assuming that one observation is drawn with replacement from each population at a time. Suppose that the sampling is terminated after n pairs of observations and k shared species were discovered, and assume that we receive payoff h(k)−cn, where h(k) is non-decreasing and the sampling cost c is non-negative. Similar to Rasmussen and Starr (1979), we show that an optimal stopping rule exists if h(k+1)−h(k) is non-increasing. An analogous result holds for group sequential sampling. This leads to using an estimate of the probability of discovering new shared species as a stopping indicator for comparing two populations with respect to the similarity index. We show by simulation and real examples that this is a feasible approach which can help to reduce the sample size.
關聯 Journal of Statistical Planning and Inference, 142(5), 1031-1039
資料類型 article
DOI http://dx.doi.org/10.1016/j.jspi.2011.10.006
dc.contributor 統計系en_US
dc.creator (作者) 余清祥zh_TW
dc.creator (作者) Yue, Jack C. ; Clayton, Murray K.-
dc.date (日期) 2012.05en_US
dc.date.accessioned 24-Jun-2014 14:58:55 (UTC+8)-
dc.date.available 24-Jun-2014 14:58:55 (UTC+8)-
dc.date.issued (上傳時間) 24-Jun-2014 14:58:55 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/66877-
dc.description.abstract (摘要) In microbial sciences, as well as other disciplines, it is often valuable to sample communities in a sequential or group sequential manner, in order to determine their structure or their similarity. We develop sequential sampling procedures to accomplish this by first assuming that one observation is drawn with replacement from each population at a time. Suppose that the sampling is terminated after n pairs of observations and k shared species were discovered, and assume that we receive payoff h(k)−cn, where h(k) is non-decreasing and the sampling cost c is non-negative. Similar to Rasmussen and Starr (1979), we show that an optimal stopping rule exists if h(k+1)−h(k) is non-increasing. An analogous result holds for group sequential sampling. This leads to using an estimate of the probability of discovering new shared species as a stopping indicator for comparing two populations with respect to the similarity index. We show by simulation and real examples that this is a feasible approach which can help to reduce the sample size.en_US
dc.format.extent 177149 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Journal of Statistical Planning and Inference, 142(5), 1031-1039en_US
dc.subject (關鍵詞) Optimal stopping; Comparing populations; Similarity index; Discovering new species; Simulationen_US
dc.title (題名) Sequential Sampling in the Search for New Shared Speciesen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.jspi.2011.10.006en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.jspi.2011.10.006 en_US