Environmental and Ecological Statistics最新文献_第4页

Spatiotemporal modelling of $$hbox {PM}_{2.5}$$ concentrations in Lombardy (Italy): a comparative study 意大利伦巴第地区 $$hbox {PM}_{2.5}$$ 浓度的时空模型：一项比较研究

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2024-02-01 DOI: 10.1007/s10651-023-00589-0

Philipp Otto, Alessandro Fusta Moro, Jacopo Rodeschini, Qendrim Shaboviq, Rosaria Ignaccolo, Natalia Golini, Michela Cameletti, Paolo Maranzano, Francesco Finazzi, Alessandro Fassò

{"title":"Spatiotemporal modelling of $$hbox {PM}_{2.5}$$ concentrations in Lombardy (Italy): a comparative study","authors":"Philipp Otto, Alessandro Fusta Moro, Jacopo Rodeschini, Qendrim Shaboviq, Rosaria Ignaccolo, Natalia Golini, Michela Cameletti, Paolo Maranzano, Francesco Finazzi, Alessandro Fassò","doi":"10.1007/s10651-023-00589-0","DOIUrl":"https://doi.org/10.1007/s10651-023-00589-0","url":null,"abstract":"This study presents a comparative analysis of three predictive models with an increasing degree of flexibility: hidden dynamic geostatistical models (HDGM), generalised additive mixed models (GAMM), and the random forest spatiotemporal kriging models (RFSTK). These models are evaluated for their effectiveness in predicting (text {PM}_{2.5}) concentrations in Lombardy (North Italy) from 2016 to 2020. Despite differing methodologies, all models demonstrate proficient capture of spatiotemporal patterns within air pollution data with similar out-of-sample performance. Furthermore, the study delves into station-specific analyses, revealing variable model performance contingent on localised conditions. Model interpretation, facilitated by parametric coefficient analysis and partial dependence plots, unveils consistent associations between predictor variables and (text {PM}_{2.5}) concentrations. Despite nuanced variations in modelling spatiotemporal correlations, all models effectively accounted for the underlying dependence. In summary, this study underscores the efficacy of conventional techniques in modelling correlated spatiotemporal data, concurrently highlighting the complementary potential of Machine Learning and classical statistical approaches.","PeriodicalId":50519,"journal":{"name":"Environmental and Ecological Statistics","volume":"50 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139667425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discrete Beta and Shifted Beta-Binomial models for rating and ranking data 用于评级和排名数据的离散贝塔模型和偏移贝塔-二叉模型

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2024-01-27 DOI: 10.1007/s10651-023-00592-5

Mariangela Sciandra, Salvatore Fasola, Alessandro Albano, Chiara Di Maria, Antonella Plaia

引用次数: 0

Advances in Kth nearest-neighbour clutter removal Kth 近邻杂波去除技术的进展

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2024-01-24 DOI: 10.1007/s10651-023-00588-1

Nicoletta D’Angelo

引用次数: 0

Logistic regression versus XGBoost for detecting burned areas using satellite images 利用卫星图像探测烧毁区域的逻辑回归与 XGBoost

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2024-01-20 DOI: 10.1007/s10651-023-00590-7

引用次数: 0

Flash floods in Mediterranean catchments: a meta-model decision support system based on Bayesian networks 地中海流域的山洪暴发：基于贝叶斯网络的元模型决策支持系统

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2024-01-09 DOI: 10.1007/s10651-023-00587-2

Rosa F. Ropero, M. Julia Flores, Rafael Rumí

引用次数: 0

A zero-inflated model for spatiotemporal count data with extra zeros: application to 1950–2015 tornado data in Kansas 具有额外零的时空计数数据的零膨胀模型：应用于 1950-2015 年堪萨斯州龙卷风数据

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2023-12-23 DOI: 10.1007/s10651-023-00586-3

Hong-Ding Yang, Audrey Chang, Wei-Wen Hsu, Chun-Shu Chen

{"title":"A zero-inflated model for spatiotemporal count data with extra zeros: application to 1950–2015 tornado data in Kansas","authors":"Hong-Ding Yang, Audrey Chang, Wei-Wen Hsu, Chun-Shu Chen","doi":"10.1007/s10651-023-00586-3","DOIUrl":"https://doi.org/10.1007/s10651-023-00586-3","url":null,"abstract":"In many tornado climate studies, the number of tornado touchdowns is often the primary outcome of interest. These outcome measures are usually generated under a spatiotemporal correlation structure and contains many zeros due to the rarity of tornado occurrence at a specific location and time interval. To model the spatiotemporal count data with excess zeros, we propose a spatiotemporal zero-inflated Poisson (ZIP) model, which lends itself to ease of interpretation and computational simplicity. Technically, we embed a modified conditional autoregressive model in the ZIP model to describe the spatial and temporal correlations, where the probability of a pure zero in the ZIP is purposely designed to depend on locations but independent of time. Illustrated with the longitudinal tornado touchdown data in the state of Kansas from 1950 to 2015, our model suggests that the spatial correlation among the counties and the corresponding temperature are significant factors attributed to the tornado touchdowns. Through the model, we can also estimate the probabilities of no tornado touchdowns for each county over time. These estimated probabilities substantially help us understand the pattern of touchdowns and further identify the risk areas across Kansas. Moreover, these estimates can be iteratively updated when more current touchdown data are available. The final model for Kansas tornado touchdown data is evaluated using more recent data.","PeriodicalId":50519,"journal":{"name":"Environmental and Ecological Statistics","volume":"78 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139030333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Are the income and price elasticities of economy-wide electricity demand in middle-income countries time-varying? Evidence from panels and individual countries 中等收入国家全经济电力需求的收入和价格弹性是否随时间变化?来自小组和个别国家的证据

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2023-11-30 DOI: 10.1007/s10651-023-00585-4

Brantley Liddle, Fakhri Hasanov

引用次数: 0

Some statistical problems involved in forecasting and estimating the spread of SARS-CoV-2 using Hawkes point processes and SEIR models 利用Hawkes点过程和SEIR模型预测和估计SARS-CoV-2传播的一些统计问题

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2023-11-29 DOI: 10.1007/s10651-023-00591-6

Frederic Schoenberg

引用次数: 0

Trade-off between efficiency and variance estimation of spatially balanced augmented samples 空间平衡增广样本的效率和方差估计之间的权衡

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2023-11-29 DOI: 10.1007/s10651-023-00582-7

Omer Ozturk, Blair L. Robertson, Olena Kravchuk, Jennifer Brown

{"title":"Trade-off between efficiency and variance estimation of spatially balanced augmented samples","authors":"Omer Ozturk, Blair L. Robertson, Olena Kravchuk, Jennifer Brown","doi":"10.1007/s10651-023-00582-7","DOIUrl":"https://doi.org/10.1007/s10651-023-00582-7","url":null,"abstract":"In this paper, we construct three types of augmented samples, which are samples generated from two separate randomization events. The first type combines a simple random sample (SRS) with a spatially balanced sample (SBS) selected from the same finite population. The second type combines an SBS with an SRS. The third type combines two spatially balanced samples. The simple random sample is constructed without replacement and does not contain any ties. The spatially balanced samples are constructed using the properties of the Halton sequence. We provide the first and second order inclusion probabilities for the augmented samples. Next, using the inclusion probabilities of the augmented samples, we construct estimators for the mean and total of a finite population. The efficiency of the augmented samples varies between the efficiency of SRS and SBS samples. If the number of SRS observations in the augmented sample is large, the efficiency is closer to the efficiency of SRS. Otherwise, it is closer to the efficiency of SBS. We also provide estimators for the variances of the estimators of population total of augmented samples. The stability of these variance estimators depends on the proportion of SRS observations in the augmented samples. The larger number of SRS observations lead to stable variance estimators.","PeriodicalId":50519,"journal":{"name":"Environmental and Ecological Statistics","volume":"34 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138533575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finding the number of latent states in hidden Markov models using information criteria 利用信息准则寻找隐马尔可夫模型中潜在状态的数量

IF 3.8 4区环境科学与生态学

Environmental and Ecological Statistics Pub Date : 2023-11-22 DOI: 10.1007/s10651-023-00584-5

Jodie Buckby, Ting Wang, David Fletcher, Jiancang Zhuang, Akiko Takeo, Kazushige Obara

{"title":"Finding the number of latent states in hidden Markov models using information criteria","authors":"Jodie Buckby, Ting Wang, David Fletcher, Jiancang Zhuang, Akiko Takeo, Kazushige Obara","doi":"10.1007/s10651-023-00584-5","DOIUrl":"https://doi.org/10.1007/s10651-023-00584-5","url":null,"abstract":"Hidden Markov models (HMMs) are often used to model time series data and are applied in many fields of research. However, estimating the unknown number of hidden states in the Markov chain is a non-trivial component of HMM model selection and an area of active research. Currently, AIC and BIC are commonly used for this purpose, despite theoretical issues and some evidence of poor performance in the literature. Here, motivated by the HMMs developed to model seismic tremor data, we use simulation studies to compare the performance of a number of model selection information criteria when used to select the number of hidden states in HMMs, including an adjusted BIC not previously used with HMMs. We find that AIC and BIC are not always reliable tools for selecting the number of hidden states in HMMs and that other information criteria such as adjusted BIC can actually perform better, depending on factors such as sample size and sojourn times in each state. We apply the information criteria to a set of HMMs fitted to seismic tremor data and compare the models selected by the different criteria.","PeriodicalId":50519,"journal":{"name":"Environmental and Ecological Statistics","volume":"101 1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138533632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0