Pub Date : 2023-05-04DOI: 10.1007/s42081-023-00203-4
Ali Saeb
{"title":"On the convergence of Shannon entropy of distribution functions in the max domain of attraction of max-stable laws","authors":"Ali Saeb","doi":"10.1007/s42081-023-00203-4","DOIUrl":"https://doi.org/10.1007/s42081-023-00203-4","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46561982","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}
Pub Date : 2023-05-02DOI: 10.33369/jsds.v2i1.24312
Muhammad Arib Alwansyah Arib
Higher education is a place to educate the next generation of the nation in terms of academic and non-academic. Basically every college tries to maximize the graduation of its students, both in quantity and quality. The undergraduate education program is targeted to complete 8 semesters of study or can also be taken in less than 8 semesters and a maximum of 14 semesters. Many factors are thought to affect the length of student study, both internal and external factors. Based on the factors that are thought to affect the length of study of the student, it is necessary to conduct research to determine what factors have a significant effect on the length of study of the student. The method that can be used to determine these factors is survival analysis using cox proportional hazard regression and random survival forest. Factors that affect the length of study using cox proportional hazard regression is GPA, while by using the random survival forest method, the factors that influence the length of study of students are GPA, gender, and part time. Based on the comparison using the C-Index method, random survival forest is a suitable method to use in the data because the C-Index error value is 26.9% which is smaller than the cox proportional hazard which is 27.8%.
{"title":"Survival Analysis of Students Not Graduated on Time Using Cox Proportional Hazard Regression Method and Random Survival Forest Method","authors":"Muhammad Arib Alwansyah Arib","doi":"10.33369/jsds.v2i1.24312","DOIUrl":"https://doi.org/10.33369/jsds.v2i1.24312","url":null,"abstract":"Higher education is a place to educate the next generation of the nation in terms of academic and non-academic. Basically every college tries to maximize the graduation of its students, both in quantity and quality. The undergraduate education program is targeted to complete 8 semesters of study or can also be taken in less than 8 semesters and a maximum of 14 semesters. Many factors are thought to affect the length of student study, both internal and external factors. Based on the factors that are thought to affect the length of study of the student, it is necessary to conduct research to determine what factors have a significant effect on the length of study of the student. The method that can be used to determine these factors is survival analysis using cox proportional hazard regression and random survival forest. Factors that affect the length of study using cox proportional hazard regression is GPA, while by using the random survival forest method, the factors that influence the length of study of students are GPA, gender, and part time. Based on the comparison using the C-Index method, random survival forest is a suitable method to use in the data because the C-Index error value is 26.9% which is smaller than the cox proportional hazard which is 27.8%.","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135270313","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}
Pub Date : 2023-04-27DOI: 10.1007/s42081-023-00206-1
O. Komori, Yusuke Saigusa, S. Eguchi
{"title":"Statistical learning for species distribution models in ecological studies","authors":"O. Komori, Yusuke Saigusa, S. Eguchi","doi":"10.1007/s42081-023-00206-1","DOIUrl":"https://doi.org/10.1007/s42081-023-00206-1","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"53297798","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}
Pub Date : 2023-04-24DOI: 10.1007/s42081-023-00202-5
Sweta Shukla, S. Lalitha
{"title":"Geographically Weighted Comedian method for spatial outlier detection","authors":"Sweta Shukla, S. Lalitha","doi":"10.1007/s42081-023-00202-5","DOIUrl":"https://doi.org/10.1007/s42081-023-00202-5","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"6 1","pages":"279 - 299"},"PeriodicalIF":1.3,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42593653","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}
Pub Date : 2023-04-20DOI: 10.1007/s42081-023-00199-x
Reza Azimi, M. Esmailian, D. Gallardo
{"title":"The inverted exponentiated Chen distribution with application to cancer data","authors":"Reza Azimi, M. Esmailian, D. Gallardo","doi":"10.1007/s42081-023-00199-x","DOIUrl":"https://doi.org/10.1007/s42081-023-00199-x","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"6 1","pages":"213 - 241"},"PeriodicalIF":1.3,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42620276","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}
Pub Date : 2023-04-11DOI: 10.1007/s42081-023-00200-7
Xiaoqiang Zeng, Y. Kakizawa
{"title":"Higher autocumulant functions for ADCINAR(1) process and bias-correction of some estimators","authors":"Xiaoqiang Zeng, Y. Kakizawa","doi":"10.1007/s42081-023-00200-7","DOIUrl":"https://doi.org/10.1007/s42081-023-00200-7","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"6 1","pages":"179 - 211"},"PeriodicalIF":1.3,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46363253","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}
Pub Date : 2023-04-04DOI: 10.1007/s42081-023-00191-5
N. Mukhopadhyay, Boyi Zhang
{"title":"Theory of new second-order expansions for the moments of $${100rho %}$$ accelerated sequential stopping times in normal mean estimation problems when $${0<rho <1}$$ is arbitrary","authors":"N. Mukhopadhyay, Boyi Zhang","doi":"10.1007/s42081-023-00191-5","DOIUrl":"https://doi.org/10.1007/s42081-023-00191-5","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42528847","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}
Pub Date : 2023-04-04DOI: 10.1007/s42081-023-00198-y
D. Fourdrinier, W. Strawderman, M. Wells
{"title":"On priors which give Bayes minimax estimators of Baranchik’s form","authors":"D. Fourdrinier, W. Strawderman, M. Wells","doi":"10.1007/s42081-023-00198-y","DOIUrl":"https://doi.org/10.1007/s42081-023-00198-y","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45236957","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}
Pub Date : 2023-03-30DOI: 10.33369/jsds.v2i1.24805
Nur Muhammad Abdul Dhohir, Tania June
Determination of evapotranspiration (ET) plays a key role in managing water in oil palm plantations. Several energy balances models have been developed for mapping evapotranspiration regionally. Subsequently, this study aims to estimate daily evapotranspiration in oil palm plantation using the METRIC model, where pixel selection used and corrected by hot and cold pixels. The climate data were collected from ERA-5 Reanalysis and Landsat 8 was used for spatial analysis. The result depicts the means ± standard deviation of ET without pixel selection (with pixel selection), specifically for oil palms age of 4, 6, 7, 8, 9, 11, 12 and 13 years were 3.19 ± 1.62 mm d-1, 3.31 ± 1.14 mm d-1, 4.01 ± 0.96 mm d-1, 4.84 ± 0.87 mm d-1, 6.29 ± 0.43 mm d-1, 5.72 ± 0.44 mm d-1, 6.43 ± 0.23 mm d-1 and 6.21 ± 0.33 mm d-1 (4.22 ± 0.49 mm d-1, 3.99 ± 0.22 mm d-1, 2.96 ± 0.34 mm d-1, 3.14 ± 0.33 mm d-1, 4.22 ± 0.49 mm d-1, 3.99 ± 0.22 mm d-1, 4.26 ± 0.24 mm d-1 and 4.18 ± 0.30 mm d-1), respectively. We have found more accurate ET determination with pixel selection (higher coefficient of determination).
{"title":"Applied Different Pixel Selection in METRIC Model for Estimating Spatial Daily Evapotranspiration of Oil Palm in East Kalimantan Province, Indonesia","authors":"Nur Muhammad Abdul Dhohir, Tania June","doi":"10.33369/jsds.v2i1.24805","DOIUrl":"https://doi.org/10.33369/jsds.v2i1.24805","url":null,"abstract":"Determination of evapotranspiration (ET) plays a key role in managing water in oil palm plantations. Several energy balances models have been developed for mapping evapotranspiration regionally. Subsequently, this study aims to estimate daily evapotranspiration in oil palm plantation using the METRIC model, where pixel selection used and corrected by hot and cold pixels. The climate data were collected from ERA-5 Reanalysis and Landsat 8 was used for spatial analysis. The result depicts the means ± standard deviation of ET without pixel selection (with pixel selection), specifically for oil palms age of 4, 6, 7, 8, 9, 11, 12 and 13 years were 3.19 ± 1.62 mm d-1, 3.31 ± 1.14 mm d-1, 4.01 ± 0.96 mm d-1, 4.84 ± 0.87 mm d-1, 6.29 ± 0.43 mm d-1, 5.72 ± 0.44 mm d-1, 6.43 ± 0.23 mm d-1 and 6.21 ± 0.33 mm d-1 (4.22 ± 0.49 mm d-1, 3.99 ± 0.22 mm d-1, 2.96 ± 0.34 mm d-1, 3.14 ± 0.33 mm d-1, 4.22 ± 0.49 mm d-1, 3.99 ± 0.22 mm d-1, 4.26 ± 0.24 mm d-1 and 4.18 ± 0.30 mm d-1), respectively. We have found more accurate ET determination with pixel selection (higher coefficient of determination).","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135464078","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}
Pub Date : 2023-03-10DOI: 10.1007/s42081-023-00190-6
S. Komukai, S. Hattori
{"title":"Asymptotic justification of maximum likelihood estimation for the proportional excess hazard model in analysis of cancer registry data","authors":"S. Komukai, S. Hattori","doi":"10.1007/s42081-023-00190-6","DOIUrl":"https://doi.org/10.1007/s42081-023-00190-6","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"6 1","pages":"337 - 359"},"PeriodicalIF":1.3,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47992448","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}
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