{"created":"2024-04-23T01:55:02.106971+00:00","id":2002495,"links":{},"metadata":{"_buckets":{"deposit":"a78f04b0-67d9-4f00-afda-56dfadeeb46c"},"_deposit":{"created_by":10,"id":"2002495","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"2002495"},"status":"published"},"_oai":{"id":"oai:fra.repo.nii.ac.jp:02002495","sets":["12:14:1716951426151"]},"author_link":["2059"],"control_number":"2002495","item_10002_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1989-02","bibliographicIssueDateType":"Issued"},"bibliographicNumberOfPages":"17","bibliographicPageEnd":"35","bibliographicPageStart":"19","bibliographicVolumeNumber":"39","bibliographic_titles":[{"bibliographic_title":"日本海区水産研究所研究報告","bibliographic_titleLang":"ja"},{"bibliographic_title":"Bulletin of the Japan Sea Regional Fisheries Research Laboratory","bibliographic_titleLang":"en"}]}]},"item_10002_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The statistical model for the PETERSEN method is a hypergeometric distribution. Approximation to a binomial distribution has been used, and the usual method for this binomial model is based on approximation to a normal distribution. The Bayesian statistical model for a binomial distribution, which assumes that the prior distribution of parameter is uniform, corresponds well with the conventional method. However, the Bayesian statistical method for a hypergeometric distribution which assumes the uniform prior distribution is not feasible. The prior distribution according to the inverse squared parameter is natural for this model. Beta function and zeta function are important to understand these methods. This model is simpler to understand and easier to calculate by micro-computer than the conventional method.","subitem_description_language":"en","subitem_description_type":"Abstract"},{"subitem_description":"ピーターセン法は超幾何分布と一致する.従来は二項分布に近似し,さらに正規分布に近似することによって区間推定を行ってきた. 母数の事前分布を一様分布と仮定するベイズ統計モデルは従来の手法とよく一致する.しかし,超幾何分布においては一様分布は事前分布として不合理である.このモデルには母数の逆二乗に従う事前分布が自然である、これらの手法を理解するためにはベータ関数とゼータ関数が重要である.このモデルは従来の手法と比較して単純で理解しやすく,小型計算機による計算も容易である.","subitem_description_language":"ja","subitem_description_type":"Abstract"}]},"item_10002_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本海区水産研究所","subitem_publisher_language":"ja"},{"subitem_publisher":"Japan Sea Regional Fisheries Research Laboratory","subitem_publisher_language":"en"}]},"item_10002_relation_16":{"attribute_name":"情報源","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"js_k_39_19_35","subitem_relation_type_select":"Local"}}]},"item_10002_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_language":"ja","subitem_relation_name_text":"日本農学文献記事索引(agriknowledge)"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://agriknowledge.affrc.go.jp/RN/2010420840","subitem_relation_type_select":"URI"}}]},"item_10002_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00186380","subitem_source_identifier_type":"NCID"}]},"item_10002_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0021-4620","subitem_source_identifier_type":"PISSN"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"Akamine, Tatsuro","creatorNameLang":"en"},{"creatorName":"赤嶺, 達郎","creatorNameLang":"ja"},{"creatorName":"アカミネ, タツロウ","creatorNameLang":"ja-Kana"}],"familyNames":[{"familyName":"Akamine","familyNameLang":"en"},{"familyName":"赤嶺","familyNameLang":"ja"},{"familyName":"アカミネ","familyNameLang":"ja-Kana"}],"givenNames":[{"givenName":"Tatsuro","givenNameLang":"en"},{"givenName":"達郎","givenNameLang":"ja"},{"givenName":"タツロウ","givenNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"2059","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"90371822","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=90371822"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Bayesian statistics; PETERSEN method; hypergeometric distribution; binomial distribution; beta function; zeta function","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"ベイズ統計によるピーターセン法の区間推定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ベイズ統計によるピーターセン法の区間推定","subitem_title_language":"ja"},{"subitem_title":"An Interval Estimation for the PETERSEN Method using Bayesian Statistics","subitem_title_language":"en"}]},"item_type_id":"10002","owner":"10","path":["1716951426151"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-04-23"},"publish_date":"2024-04-23","publish_status":"0","recid":"2002495","relation_version_is_last":true,"title":["ベイズ統計によるピーターセン法の区間推定"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2025-04-01T05:17:23.403341+00:00"}