start-ver=1.4
cd-journal=joma
no-vol=4
cd-vols=
no-issue=1
article-no=
start-page=7
end-page=18
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=1999
dt-pub=19990226
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Swap-Rate of Entrance Examination and Its Software -SRAS-
kn-title=合否入れ替わり率とその解析ソフトウェアSRAS
en-subtitle=
kn-subtitle=
en-abstract=When we select N? student from N applicants using a result of an entrance examination, which consists of two step selection, the primary test and the secondary test. It is important to evaluate the contribution for each test. Swap-rate is one of the measure of the contribution for each stage test, and it its widely used. In this paper, we describe a population swap-rate and a sample swap-rate in the first. Next, we consider the distribution of applicants who change the result of the test from pass to fail. Finary, we introduce our system "SRAS - Swap-Rate Analysis System-", that can analyze the examination data on such point of view.
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=1
ORCID=

en-aut-name=YamamotoYoshiro
en-aut-sei=Yamamoto
en-aut-mei=Yoshiro
kn-aut-name=山本義郎
kn-aut-sei=山本
kn-aut-mei=義郎
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
END

start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=1
article-no=
start-page=43
end-page=49
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2008
dt-pub=200803
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Estimate of the posted land price in Okayama city and its visualizing system
kn-title=岡山市における地価公示価格の推定とその表示システムについて
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The posted land price is a decrared land price from Land Appraisal Committee, and current market price is selling price of the market.
In this paper, we investigate the methods to estimate land price from the posted land price in Okayama city, and create the visualizing system of the price on.
en-copyright=
kn-copyright=

en-aut-name=NakaoKazuo
en-aut-sei=Nakao
en-aut-mei=Kazuo
kn-aut-name=中尾一生
kn-aut-sei=中尾
kn-aut-mei=一生
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=Land price
kn-keyword=Land price
en-keyword=Google maps
kn-keyword=Google maps
en-keyword=GIS
kn-keyword=GIS
en-keyword=Ajax
kn-keyword=Ajax
END

start-ver=1.4
cd-journal=joma
no-vol=13
cd-vols=
no-issue=1
article-no=
start-page=17
end-page=22
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2008
dt-pub=200803
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Spatial analysis of Kawaguchi City crime data
kn-title=川口市犯罪データの空間分析
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=In this paper, we built some models of the spatial data, and evaluate those, using the crime data of　Kawaguchi city, Saitama prefecture in Japan. Compute the Moran’I statistics of five crime data related to thefts in the city, the value of sneakthief take the aggregation. So, we pay attention to the sneak, and make a model to estimate the incidence of the events. As a regression, we select the old-age index　among regional indexes. Applying a simple regression(SR), a spatial autoregressive model(SAR), a　geographically weighted regression(GWR) , we evaluate these models. In GWR model, it is interesting that there are some sections in which the sign of the coefficient takes the opposite versus SR and SAR
models. So, stratifying the data by the sign of it, we investigate to data precisely.
en-copyright=
kn-copyright=

en-aut-name=OhshimoYuki
en-aut-sei=Ohshimo
en-aut-mei=Yuki
kn-aut-name=大下優夫
kn-aut-sei=大下
kn-aut-mei=優夫
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=crime data
kn-keyword=crime data
en-keyword=Kawaguchi city
kn-keyword=Kawaguchi city
en-keyword=spatial analysis
kn-keyword=spatial analysis
en-keyword=spatial autoregressive model
kn-keyword=spatial autoregressive model
en-keyword=geographically weighted regression
kn-keyword=geographically weighted regression
END

start-ver=1.4
cd-journal=joma
no-vol=3
cd-vols=
no-issue=1
article-no=
start-page=37
end-page=46
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=1998
dt-pub=19980114
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Assessing Local Influence in Multivariate Analyses of Incomplete Data
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The present paper deals with multivariate analyses applied to the maximum likelihood estimate(s) for (the mean vector and) the covariance matrix based on incomplete data, and derives influence functions for the mean vector, the covariance matrix and some statistics in multivariate analyses. Influential directions in the sense of Cook's local influence are also derived. A numerical example is given to show the usefulness of the proposed method.
en-copyright=
kn-copyright=

en-aut-name=
en-aut-sei=
en-aut-mei=
kn-aut-name=KimHyum-Jeong
kn-aut-sei=Kim
kn-aut-mei=Hyum-Jeong
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

en-aut-name=TanakaYutaka
en-aut-sei=Tanaka
en-aut-mei=Yutaka
kn-aut-name=田中豊
kn-aut-sei=田中
kn-aut-mei=豊
aut-affil-num=3
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学

affil-num=3
en-affil=
kn-affil=岡山大学
END

start-ver=1.4
cd-journal=joma
no-vol=8
cd-vols=
no-issue=1
article-no=
start-page=9
end-page=17
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2003
dt-pub=200303
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Development of a statistical survey analysis system using Internet
kn-title=インターネットを利用した統計調査分析システムの構築
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=We constructed the online analysis system of the Okayama Activity Area Survey in place since 1979. This is one way to solve the problem in case of releasing the result of a statistical survey. In this paper, we treat the detail of the structure of the system.
en-copyright=
kn-copyright=

en-aut-name=FujinoTomokazu
en-aut-sei=Fujino
en-aut-mei=Tomokazu
kn-aut-name=藤野友和
kn-aut-sei=藤野
kn-aut-mei=友和
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=microdata
kn-keyword=microdata
en-keyword=statistical disclosure control
kn-keyword=statistical disclosure control
en-keyword=web based system
kn-keyword=web based system
en-keyword=online database
kn-keyword=online database
END

start-ver=1.4
cd-journal=joma
no-vol=10
cd-vols=
no-issue=1
article-no=
start-page=41
end-page=47
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2005
dt-pub=20050228
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Variable Selection Method using Apriori Algorithm on Contingency Table
kn-title=分割表データにおけるApriori Alogrihtmを利用した変数選択手法
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=We proposed a new applied method for induction of variable selection on contingency table. This method is the application of Apriori algorithm on variable selection of contigency table with iteraction. We assume that variables are dichotomous variable. We confirm that can be select variable, when minimun support is low level by using AIC on variable selection criterion.
en-copyright=
kn-copyright=

en-aut-name=OhnoManabu
en-aut-sei=Ohno
en-aut-mei=Manabu
kn-aut-name=大野学
kn-aut-sei=大野
kn-aut-mei=学
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=Apriori Algorithm
kn-keyword=Apriori Algorithm
en-keyword=Varable Selection
kn-keyword=Varable Selection
en-keyword=Contigency Table
kn-keyword=Contigency Table
en-keyword=Interaction
kn-keyword=Interaction
END

start-ver=1.4
cd-journal=joma
no-vol=9
cd-vols=
no-issue=1
article-no=
start-page=9
end-page=17
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2004
dt-pub=20040227
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Small Geographic Area Estimation in WinBUGS with Two Approaches Prediction
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Small Area Estimation (SAE) is the process of using statistical models to link survey outcome variables to a set of predictor variables known for small domains, in order to predict domain-level estimates. The need for detailed statistics on small area is constantly increasing. Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics from both public and private sectors. Bayesian hierarchical models provide a convenient framework for disease mapping and geographical correlation studies. Computation may be carried out using the freely-available WinBUGS software. Two approaches prediction to estimate total patient in small area i will be presented. For the purpose of this paper, the small area estimation in this context use data of Indnesia's population based on the 2000 census for the population of Jakarta and data of patient diarrhea from District Health Service of Jakarta. We interest to predict total patient of diarrhea as variable of interest and data population as auxiliary data from unsample for each small area.
en-copyright=
kn-copyright=

en-aut-name=
en-aut-sei=
en-aut-mei=
kn-aut-name=SetiawanAgus
kn-aut-sei=Setiawan
kn-aut-mei=Agus
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=Auxiliary data
kn-keyword=Auxiliary data
en-keyword=Population density
kn-keyword=Population density
en-keyword=Sample survey
kn-keyword=Sample survey
en-keyword=Small area estimation
kn-keyword=Small area estimation
en-keyword=WinBUGS
kn-keyword=WinBUGS
END

start-ver=1.4
cd-journal=joma
no-vol=9
cd-vols=
no-issue=1
article-no=
start-page=1
end-page=7
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2004
dt-pub=20040227
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Development of the Mesh Data Analysis System
kn-title=地域メッシュデータ分析システムの開発
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Area mesh statistics is a kind of small area statistics. The area mesh data of Japan can be created in a lot of way and many of them can be downloaded, for example, from the land's value information service which is provided by Ministry of Land, Infrastructure and Transport of Japan. We developed database of these area mesh data. By using mesh navigator software (Makita Naoki, 1997), which needs to run on ProAtlas2000 and Microsoft Access2000, we displayed the mesh data on the map. What visualized on the map is very convenient. For extending the advantages of area mesh data to spatial geographical statistics, we used PostgreSQL to develop a new database of mesh data. We also develop some programs in Delphi for the analysis of area mesh data, such as Histogram, Echelon analysis, and etc.
en-copyright=
kn-copyright=

en-aut-name=NiuDonghui
en-aut-sei=Niu
en-aut-mei=Donghui
kn-aut-name=牛冬慧
kn-aut-sei=牛
kn-aut-mei=冬慧
aut-affil-num=1
ORCID=

en-aut-name=TarumiTomoyuki
en-aut-sei=Tarumi
en-aut-mei=Tomoyuki
kn-aut-name=垂水共之
kn-aut-sei=垂水
kn-aut-mei=共之
aut-affil-num=2
ORCID=

affil-num=1
en-affil=
kn-affil=岡山大学

affil-num=2
en-affil=
kn-affil=岡山大学
en-keyword=Area mesh data
kn-keyword=Area mesh data
en-keyword=PostgreSQL
kn-keyword=PostgreSQL
en-keyword=PQCompo
kn-keyword=PQCompo
en-keyword=ProAtlas2000
kn-keyword=ProAtlas2000
END