Journal of Agricultural Biological and Environmental Statistics最新文献_第5页

Review of “Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting” by Anuradha Tomar, Prerna Gaur, and Xiaolong Jin (Editors) 《可再生能源发电和负荷需求预测技术》综述(编者:Anuradha Tomar, Prerna Gaur, xiadragon Jin)

4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-09-19 DOI: 10.1007/s13253-023-00569-8

Dani Pasaribu, Alrend Roy Peterson Kaputing, Delvianus Kaesmentan

引用次数: 0

3D Point Cloud Semantic Segmentation Through Functional Data Analysis 基于功能数据分析的三维点云语义分割

4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-09-12 DOI: 10.1007/s13253-023-00567-w

Manuel Oviedo de la Fuente, Carlos Cabo, Javier Roca-Pardiñas, E. Louise Loudermilk, Celestino Ordóñez

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引用次数: 0

J. A. Diehl and H. Kaur (Eds.): New Forms of Urban Agriculture: An Urban Ecology Perspective—A Book Review J. A. Diehl和H. Kaur(编):都市农业的新形式:城市生态学的视角——书评

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-09-05 DOI: 10.1007/s13253-023-00568-9

Prodipto Bishnu Angon

引用次数: 0

Clustered and Unclustered Group Testing for Biosecurity 生物安全的聚类和非聚类组测试

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-08-26 DOI: 10.1007/s13253-023-00566-x

R. Clark, B. Barnes, M. Parsa

引用次数: 0

Environmental Public Policy Making Exposed, Cynthia H. Stahl, Alan J. Cimorelli, Switzerland: Springer Nature Switzerland AG (2020). 203 pp, ISBN 978-3-030–32130-7 (eBook) 《环境公共政策制定》，辛西娅·h·斯塔尔，艾伦·j·西莫雷利，瑞士:施普林格·自然瑞士股份有限公司(2020)。203 pp, ISBN 978-3-030-32130-7(电子书)

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-08-26 DOI: 10.1007/s13253-023-00556-z

Edyanto, L. Arifin, Syaharuddin

引用次数: 0

A Nonparametric Bootstrap Method for Heteroscedastic Functional Data 异方差泛函数据的非参数自举法

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-08-16 DOI: 10.1007/s13253-023-00561-2

R. Fernández-Casal, Sergio Castillo-Páez, Miguel Flores

引用次数: 0

An Application of Spatio-temporal Modeling to Finite Population Abundance Prediction. 时空建模在有限种群丰度预测中的应用。

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-08-07 DOI: 10.1007/s13253-023-00565-y

Matt Higham, Michael Dumelle, Carly Hammond, Jay Ver Hoef, Jeff Wells

{"title":"An Application of Spatio-temporal Modeling to Finite Population Abundance Prediction.","authors":"Matt Higham, Michael Dumelle, Carly Hammond, Jay Ver Hoef, Jeff Wells","doi":"10.1007/s13253-023-00565-y","DOIUrl":"10.1007/s13253-023-00565-y","url":null,"abstract":"<p><p>Spatio-temporal models can be used to analyze data collected at various spatial locations throughout multiple time points. However, even with a finite number of spatial locations, there may be a lack of resources to collect data from every spatial location at every time point. We develop a spatio-temporal finite-population block kriging (ST-FPBK) method to predict a quantity of interest, such as a mean or total, across a finite number of spatial locations. This ST-FPBK predictor incorporates an appropriate variance reduction for sampling from a finite population. Through an application to moose surveys in the east-central region of Alaska, we show that the predictor has a substantially smaller standard error compared to a predictor from the purely spatial model that is currently used to analyze moose surveys in the region. We also show how the model can be used to forecast a prediction for abundance in a time point for which spatial locations have not yet been surveyed. A separate simulation study shows that the spatio-temporal predictor is unbiased and that prediction intervals from the ST-FPBK predictor attain appropriate coverage. For ecological monitoring surveys completed with some regularity through time, use of ST-FPBK could improve precision. We also give an R package that ecologists and resource managers could use to incorporate data from past surveys in predicting a quantity from a current survey.</p>","PeriodicalId":56336,"journal":{"name":"Journal of Agricultural Biological and Environmental Statistics","volume":"28 3","pages":"1-25"},"PeriodicalIF":1.4,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimator of Agreement with Covariate Adjustment 协变量调整的一致性估计

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-08-05 DOI: 10.1007/s13253-023-00553-2

Katelyn A. McKenzie, J. Mahnken

引用次数: 0

Spatially Clustered Survey Designs 空间聚类调查设计

IF 1.4 4区数学

Journal of Agricultural Biological and Environmental Statistics Pub Date : 2023-07-28 DOI: 10.1007/s13253-023-00562-1

S. Foster, E. Lawrence, A. Hoskins

引用次数: 0

Presence-Only for Marked Point Process Under Preferential Sampling 优先抽样下标记点过程的只存在性