Spatial Statistics最新文献_第4页

Navigating challenges in spatio-temporal modelling of Antarctic krill abundance: Addressing zero-inflated data and misaligned covariates 南极磷虾丰度时空建模中的导航挑战：解决零膨胀数据和错位协变量

IF 2.5 2区数学

Spatial Statistics Pub Date : 2025-12-01 Epub Date: 2025-09-26 DOI: 10.1016/j.spasta.2025.100937

André Victor Ribeiro Amaral , Adam M. Sykulski , Sophie Fielding , Emma Cavan

{"title":"Navigating challenges in spatio-temporal modelling of Antarctic krill abundance: Addressing zero-inflated data and misaligned covariates","authors":"André Victor Ribeiro Amaral , Adam M. Sykulski , Sophie Fielding , Emma Cavan","doi":"10.1016/j.spasta.2025.100937","DOIUrl":"10.1016/j.spasta.2025.100937","url":null,"abstract":"<div><div>Antarctic krill (<em>Euphausia superba</em>) are among the most abundant species on our planet and serve as a vital food source for many marine predators in the Southern Ocean. In this paper, we utilise statistical spatio-temporal methods to combine data from various sources and resolutions, aiming to model krill abundance. Our focus lies in fitting the model to a dataset comprising acoustic measurements of krill biomass. To achieve this, we integrate climate covariates obtained from satellite imagery and from drifting surface buoys (also known as drifters). Additionally, we use sparsely collected krill biomass data obtained from net fishing efforts (KRILLBASE) for validation. However, integrating these multiple heterogeneous data sources presents significant modelling challenges, including spatio-temporal misalignment and inflated zeros in the observed data. To address these challenges, we fit a Hurdle-Gamma model to jointly describe the occurrence of zeros and the krill biomass for the non-zero observations, while also accounting for misaligned and heterogeneous data sources, including drifters. Therefore, our work presents a comprehensive framework for analysing and predicting krill abundance in the Southern Ocean, leveraging information from various sources and formats. This is crucial due to the impact of krill fishing, as understanding their distribution is essential for informed management decisions and fishing regulations aimed at protecting the species.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"70 ","pages":"Article 100937"},"PeriodicalIF":2.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic spatial regimes for spatial panel data 空间面板数据的动态空间机制

IF 2.5 2区数学

Spatial Statistics Pub Date : 2025-12-01 Epub Date: 2025-11-01 DOI: 10.1016/j.spasta.2025.100939

Anna Gloria Billé , Roberto Benedetti , Paolo Postiglione

引用次数: 0

Spatial survival models based on Weibull random fields 基于威布尔随机场的空间生存模型

IF 2.5 2区数学

Spatial Statistics Pub Date : 2025-12-01 Epub Date: 2025-11-07 DOI: 10.1016/j.spasta.2025.100943

Christian Caamaño-Carrillo , Moreno Bevilacqua , Diego I. Gallardo

{"title":"Spatial survival models based on Weibull random fields","authors":"Christian Caamaño-Carrillo , Moreno Bevilacqua , Diego I. Gallardo","doi":"10.1016/j.spasta.2025.100943","DOIUrl":"10.1016/j.spasta.2025.100943","url":null,"abstract":"<div><div>We propose a novel spatial survival model based on a Weibull random field, designed to overcome the limitations of existing copula-based approaches; particularly those relying on the Farlie–Gumbel–Morgenstern (FGM) copula. Although the FGM model only captures weak dependence and enforces reflection symmetry and a forced nugget effect, our model allows for stronger spatial dependence, reflection asymmetry, and mean-square continuity. These properties provide a more flexible and realistic framework for analyzing spatially correlated time-to-event data. The model unifies the proportional hazards (PH), the accelerated failure time (AFT), and the mean parameterizations of the Weibull distribution, allowing a clear interpretation of the effects of the covariates. Due to the analytical intractability of the full likelihood, parameter estimation is performed using a weighted pairwise composite likelihood method based on nearest neighbors. This method offers computational efficiency and robustness to right-censored data. Simulation studies confirm the effectiveness of the proposed model, and an application to real housing data illustrates its practical value.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"70 ","pages":"Article 100943"},"PeriodicalIF":2.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A concordance coefficient for lattice data: An application to poverty indices in Chile 格点数据的一致性系数：在智利贫困指数中的应用

IF 2.5 2区数学

Spatial Statistics Pub Date : 2025-12-01 Epub Date: 2025-09-27 DOI: 10.1016/j.spasta.2025.100936

Ronny Vallejos , Clemente Ferrer , Jorge Mateu

引用次数: 0

Conformal novelty detection for replicate point patterns with FDR or FWER control 用FDR或FWER控制复制点模式的保形新颖性检测

IF 2.5 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-08-05 DOI: 10.1016/j.spasta.2025.100924

Christophe A.N. Biscio , Adrien Mazoyer , Martin V. Vejling

{"title":"Conformal novelty detection for replicate point patterns with FDR or FWER control","authors":"Christophe A.N. Biscio , Adrien Mazoyer , Martin V. Vejling","doi":"10.1016/j.spasta.2025.100924","DOIUrl":"10.1016/j.spasta.2025.100924","url":null,"abstract":"<div><div>Monte Carlo tests are widely used for computing valid <span><math><mi>p</mi></math></span>-values without requiring known distributions of test statistics. When performing multiple Monte Carlo tests, it is essential to maintain control of the type I error. Some techniques for multiplicity control pose requirements on the joint distribution of the <span><math><mi>p</mi></math></span>-values, for instance independence, which can be computationally intensive to achieve, as it requires simulating disjoint null samples for each test. We refer to this as naïve multiple Monte Carlo testing. We highlight in this work that multiple Monte Carlo testing is an instance of conformal novelty detection. Leveraging this insight enables a more efficient multiple Monte Carlo testing procedure, avoiding excessive simulations by using a single null sample for all the tests, while still ensuring exact control over the false discovery rate or the family-wise error rate. We call this approach conformal multiple Monte Carlo testing. The performance is investigated in the context of global envelope tests for point pattern data through a simulation study and an application to a sweat gland data set. Results reveal that with a fixed simulation budget, our proposed method yields substantial improvements in power of the testing procedure as compared to the naïve multiple Monte Carlo testing procedure.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"69 ","pages":"Article 100924"},"PeriodicalIF":2.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial robust fuzzy clustering of mixed data with electoral study 基于选举研究的混合数据空间鲁棒模糊聚类

IF 2.1 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-07-02 DOI: 10.1016/j.spasta.2025.100914

Domenico Cangemi , Pierpaolo D’Urso , Livia De Giovanni , Lorenzo Federico , Vincenzina Vitale

引用次数: 0

Estimation and testing of time-varying coefficients spatial autoregressive panel data model 时变系数空间自回归面板数据模型的估计与检验

IF 2.1 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-07-24 DOI: 10.1016/j.spasta.2025.100922

Lingling Tian , Chuanhua Wei , Wenxing Ding , Mixia Wu

引用次数: 0

A two-step sampling strategy to improve the prediction accuracy of contamination hotspots and identify hotspot boundaries 采用两步采样策略提高污染热点预测精度并识别热点边界

IF 2.1 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-07-07 DOI: 10.1016/j.spasta.2025.100918

Joonmyoung Kim , Seonwoo Lee , Taekseon Ryu , Jonghyun Na , Taehyun Yun , Jeongho Lee , Hansuk Kim , Man Jae Kwon , Ho Young Jo , Yongsung Joo

{"title":"A two-step sampling strategy to improve the prediction accuracy of contamination hotspots and identify hotspot boundaries","authors":"Joonmyoung Kim , Seonwoo Lee , Taekseon Ryu , Jonghyun Na , Taehyun Yun , Jeongho Lee , Hansuk Kim , Man Jae Kwon , Ho Young Jo , Yongsung Joo","doi":"10.1016/j.spasta.2025.100918","DOIUrl":"10.1016/j.spasta.2025.100918","url":null,"abstract":"<div><div>Efficient soil remediation, both economically and environmentally, depends on accurate mapping of contaminant concentrations and boundaries of hotspots (areas with concentrations exceeding a critical threshold) through an effective allocation of limited soil sampling sites. This paper introduces a novel two-step sampling location selection method, referred to as the weighted stepwise spatial sampling (WSSS) method. The WSSS method is specifically designed to provide accurate estimates of contaminant concentrations within hotspots and their boundaries. In the first step, dispersed sampling locations are selected for broad exploration, while in the second step, guided by the digital soil mapping results based on the first-step sampling data, sampling locations are selected to focus on identifying potential hotspots. A simulation study using total petroleum hydrocarbon soil data from South Korea demonstrates the superior accuracy and stability of the WSSS in identifying hotspot boundaries and predicting contaminant concentrations within hotspots, compared to other sampling location selection methods. This performance is achieved through an objective function specifically designed to ensure that the selection of sampling locations in the second step is robust to potential inaccuracies or uncertainties in the initial predictions.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"69 ","pages":"Article 100918"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sampling design for binary geostatistical data, application to inspection actions of fishing activity in Portugal 二元地质统计数据的抽样设计，在葡萄牙渔业活动检查行动中的应用

IF 2.1 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-07-21 DOI: 10.1016/j.spasta.2025.100919

Belchior Miguel , Paula Simões , Rui Gonçalves de Deus , Isabel Natário

{"title":"Sampling design for binary geostatistical data, application to inspection actions of fishing activity in Portugal","authors":"Belchior Miguel , Paula Simões , Rui Gonçalves de Deus , Isabel Natário","doi":"10.1016/j.spasta.2025.100919","DOIUrl":"10.1016/j.spasta.2025.100919","url":null,"abstract":"<div><div>The definition of surveillance routes is a very important but complex issue. The Portuguese Navy, in its common form of operation is in charge of the Naval Standard Device, which is distributed throughout the various coastal areas of the country. Enforcement actions can involve very high costs, so a good plan for the sampling designs used are in order, as to maximize the efficiency in obtaining information from the data of the actions developed over the area under consideration. The main objective of this study is to propose sampling design criteria based on geostatistical models, in the context of binary data on presumed maritime infractions in the Portuguese coast, that are advantageous in the optimization of maritime surveillance actions, in terms of efforts employed in their execution, in the maritime area of Portugal’s responsibility. Two sampling design selection criteria are proposed: Maximum Risk Sampling design and Maximum Variance Risk Sampling Design. These are compared to the simple random design by the root mean square error (RMSE). A comparison of the designs at different sample sizes is made and the estimated risk maximization sampling design presents the best RMSE value. The proposed sampling designs may assist in the creation of alternative enforcement Portuguese Navy routes, optimizing the scheduling that maximizes the probability of finding a higher number of presumed fishing perpetrators with less resource efforts.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"69 ","pages":"Article 100919"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geographically informed graph neural networks 地理信息图神经网络

IF 2.1 2区数学

Spatial Statistics Pub Date : 2025-10-01 Epub Date: 2025-07-15 DOI: 10.1016/j.spasta.2025.100920

Xuankai Ma , Zehua Zhang , Yongze Song

{"title":"Geographically informed graph neural networks","authors":"Xuankai Ma , Zehua Zhang , Yongze Song","doi":"10.1016/j.spasta.2025.100920","DOIUrl":"10.1016/j.spasta.2025.100920","url":null,"abstract":"<div><div>Graph neural networks (GNNs) have been introduced to spatial statistical tasks due to their mechanisms of simulating spatial interactions and processes among geographical neighbours using graph structures. However, previous methods ignore quantifying differences in attributes among adjacent spatial characteristics. Considering this spatial characteristic by fitting the spatial statistic trinity (SST) framework may help improve models’ accuracy and robustness. Thus, we introduce the geographically informed graph neural network (GIGNN) by considering the additional geospatial feature: closer geographical entities may interact less when spatial disparities are captured. When setting up the model, GIGNN leverages differences of attributes by spatial stratified heterogeneity, quantifies connections between geographical entities, and inherits k-order neighbour attribute aggregation and message-passing mechanisms from GNNs. GIGNN is applied to an urbanization analysis study in the Greater Perth Area, Australia, showing higher accuracy than the existing machine learning models and other GNNs in simulation and prediction accuracy. GIGNN achieved an accuracy of 84.1% for simulation and an accuracy of 81% for prediction. Incorporating spatial characteristics into GNNs enhances simulation and prediction accuracy in geoscientific applications, highlighting the importance of spatially aware models in solving complex problems by capturing geographical data dependencies.</div></div>","PeriodicalId":48771,"journal":{"name":"Spatial Statistics","volume":"69 ","pages":"Article 100920"},"PeriodicalIF":2.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0