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Content
September 2023, Volume 34, Issue 6
- e2799 Multistage hierarchical capture–recapture models
by Mevin B. Hooten & Michael R. Schwob & Devin S. Johnson & Jacob S. Ivan - e2800 Subordinated Gaussian processes for solar irradiance
by Caitlin M. Berry & William Kleiber & Bri‐Mathias Hodge - e2802 Assessing the ability of adaptive designs to capture trends in hard coral cover
by AWLP Thilan & P Menéndez & JM McGree - e2803 CO2 has significant implications for hourly ambient temperature: Evidence from Hawaii
by Kevin F. Forbes - e2819 Air pollution estimation under air stagnation—A case study of Beijing
by Ying Zhang & Song Xi Chen & Le Bao
August 2023, Volume 34, Issue 5
- e2792 Nonlinear prediction of functional time series
by Haixu Wang & Jiguo Cao - e2793 CO2 emissions and growth: A bivariate bidimensional mean‐variance random effects model
by Antonello Maruotti & Pierfrancesco Alaimo Di Loro - e2797 New estimation methods for extremal bivariate return curves
by C. J. R. Murphy‐Barltrop & J. L. Wadsworth & E. F. Eastoe - e2798 Approximation of Bayesian Hawkes process with inlabru
by Francesco Serafini & Finn Lindgren & Mark Naylor - e2817 Long memory conditional random fields on regular lattices
by Angela Ferretti & L. Ippoliti & P. Valentini & R. J. Bhansali
June 2023, Volume 34, Issue 4
- e2753 Principal component analysis for river network data: Use of spatiotemporal correlation and heterogeneous covariance structure
by Kyusoon Kim & Hee‐Seok Oh & Minsu Park - e2765 Functional forecasting of dissolved oxygen in high‐frequency vertical lake profiles
by Luke Durell & J. Thad Scott & Douglas Nychka & Amanda S. Hering - e2775 Bayesian multiple changepoint detection with missing data and its application to the magnitude‐frequency distributions
by Shaochuan Lu - e2782 Stable sums to infer high return levels of multivariate rainfall time series
by Gloria Buriticá & Philippe Naveau - e2786 A Bayesian time series model for reconstructing hydroclimate from multiple proxies
by Niamh Cahill & Jacky Croke & Micheline Campbell & Kate Hughes & John Vitkovsky & Jack Eaton Kilgallen & Andrew Parnell - e2801 Mitigating spatial confounding by explicitly correlating Gaussian random fields
by Isa Marques & Thomas Kneib & Nadja Klein
May 2023, Volume 34, Issue 3
- e2779 Families of complex‐valued covariance models through integration
by Sandra De Iaco - e2785 Multivariate receptor modeling with widely dispersed Lichens as bioindicators of air quality
by Matthew Heiner & Taylor Grimm & Hayden Smith & Steven D. Leavitt & William F. Christensen & Gregory T. Carling & Larry L. St. Clair - e2794 A Bayesian change point modeling approach to identify local temperature changes related to urbanization
by C. Berrett & B. Gurney & D. Arthur & T. Moon & G. P. Williams - e2795 Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada
by Fatima Palacios‐Rodriguez & Elena Di Bernardino & Melina Mailhot - e2796 Comparing emulation methods for a high‐resolution storm surge model
by Grant Hutchings & Bruno Sansó & James Gattiker & Devin Francom & Donatella Pasqualini
March 2023, Volume 34, Issue 2
- e2731 Intersection between environmental data science and the R community in Latin America
by Natalia da Silva - e2732 Framing data science, analytics and statistics around the digital earth concept
by E. Marian Scott - e2749 Data science and climate risk analytics
by Stephan R. Sain - e2754 Emulation of greenhouse‐gas sensitivities using variational autoencoders
by Laura Cartwright & Andrew Zammit‐Mangion & Nicholas M. Deutscher - e2756 Pesticide concentration monitoring: Investigating spatio‐temporal patterns in left censored data
by Clément Laroche & Madalina Olteanu & Fabrice Rossi - e2758 On the selection of an interpolation method with an application to the Fire Weather Index in Ontario, Canada
by Kevin Granville & Douglas G. Woolford & C. B. Dean & Dennis Boychuk & Colin B. McFayden - e2759 Spatiotemporal modeling of mature‐at‐length data using a sliding window approach
by Yuan Yan & Eva Cantoni & Chris Field & Margaret Treble & Joanna Mills Flemming - e2761 Shooting for abundance: Comparing integrated multi‐sampling models for camera trap and hair trap data
by Mehnaz Jahid & Holly N. Steeves & Jason T. Fisher & Simon J. Bonner & Saman Muthukumarana & Laura L. E. Cowen - e2769 Flood hazard model calibration using multiresolution model output
by Samantha M. Roth & Ben Seiyon Lee & Sanjib Sharma & Iman Hosseini‐Shakib & Klaus Keller & Murali Haran - e2778 A Bayesian framework for studying climate anomalies and social conflicts
by Ujjal Kumar Mukherjee & Benjamin E. Bagozzi & Snigdhansu Chatterjee - e2784 Estimating functional single index models with compact support
by Yunlong Nie & Liangliang Wang & Jiguo Cao - e2788 Environmental data science: Part 2
by Wesley S. Burr & Nathaniel K. Newlands & Andrew Zammit‐Mangion - e2789 The role of data science in environmental digital twins: In praise of the arrows
by Gordon S. Blair & Peter A. Henrys
February 2023, Volume 34, Issue 1
- e2745 Uncertainty: Nothing is more certain
by Sally Cripps & Hugh Durrant‐Whyte - e2748 Conjugate sparse plus low rank models for efficient Bayesian interpolation of large spatial data
by Shinichiro Shirota & Andrew O. Finley & Bruce D. Cook & Sudipto Banerjee - e2757 Scalable spatio‐temporal smoothing via hierarchical sparse Cholesky decomposition
by Marcin Jurek & Matthias Katzfuss - e2762 Detecting changes in mixed‐sampling rate data sequences
by Aaron Paul Lowther & Rebecca Killick & Idris Arthur Eckley - e2763 A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution
by Oliver Baerenbold & Melanie Meis & Israel Martínez‐Hernández & Carolina Euán & Wesley S. Burr & Anja Tremper & Gary Fuller & Monica Pirani & Marta Blangiardo - e2766 Stochastic tropical cyclone precipitation field generation
by William Kleiber & Stephan Sain & Luke Madaus & Patrick Harr - e2767 Decisions, decisions, decisions in an uncertain environment
by Noel Cressie - e2770 Large‐scale environmental data science with ExaGeoStatR
by Sameh Abdulah & Yuxiao Li & Jian Cao & Hatem Ltaief & David E. Keyes & Marc G. Genton & Ying Sun - e2771 A double fixed rank kriging approach to spatial regression models with covariate measurement error
by Xu Ning & Francis K. C. Hui & Alan H. Welsh - e2772 An illustration of model agnostic explainability methods applied to environmental data
by Christopher K. Wikle & Abhirup Datta & Bhava Vyasa Hari & Edward L. Boone & Indranil Sahoo & Indulekha Kavila & Stefano Castruccio & Susan J. Simmons & Wesley S. Burr & Won Chang - e2773 The scope of the Kalman filter for spatio‐temporal applications in environmental science
by Jonathan Rougier & Aoibheann Brady & Jonathan Bamber & Stephen Chuter & Sam Royston & Bramha Dutt Vishwakarma & Richard Westaway & Yann Ziegler - e2780 REDS: Random ensemble deep spatial prediction
by Ranadeep Daw & Christopher K. Wikle - e2783 Data science applied to environmental sciences
by Paulo Canas Rodrigues & Elisabetta Carfagna - e2787 Environmental data science: Part 1
by Andrew Zammit‐Mangion & Nathaniel K. Newlands & Wesley S. Burr
December 2022, Volume 33, Issue 8
- e2760 Mechanistic spatial models for heavy metal pollution
by Wilson J. Wright & Peter N. Neitlich & Alyssa E. Shiel & Mevin B. Hooten - e2768 Two years of COVID‐19 pandemic: The Italian experience of Statgroup‐19
by Giovanna Jona Lasinio & Fabio Divino & Gianfranco Lovison & Marco Mingione & Pierfrancesco Alaimo Di Loro & Alessio Farcomeni & Antonello Maruotti - e2774 Modeling the spatial evolution wildfires using random spread process
by Carlos Díaz‐Avalos & Pablo Juan - e2776 Sequential spatially balanced sampling
by Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé - e2777 Record events attribution in climate studies
by Julien Worms & Philippe Naveau - e2781 A vector of point processes for modeling interactions between and within species using capture‐recapture data
by Alex Diana & Eleni Matechou & Jim E. Griffin & Yadvendradev Jhala & Qamar Qureshi
November 2022, Volume 33, Issue 7
- e2746 A note on statistical tests for homogeneities in multivariate extreme value models for block maxima
by Jona Lilienthal & Leandra Zanger & Axel Bücher & Roland Fried - e2750 From model selection to maps: A completely design‐based data‐driven inference for mapping forest resources
by Rosa Maria Di Biase & Lorenzo Fattorini & Sara Franceschi & Mirko Grotti & Nicola Puletti & Piermaria Corona - e2751 Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes
by Lauren Hoskovec & Sheena Martenies & Tori L. Burket & Sheryl Magzamen & Ander Wilson - e2752 Changepoint detection in autocorrelated ordinal categorical time series
by Mo Li & QiQi Lu - e2755 Clustering of bivariate satellite time series: A quantile approach
by Victor Muthama Musau & Carlo Gaetan & Paolo Girardi - e2764 Regression methods for the appearances of extremes in climate data
by Chang Yu & Ondrej Blaha & Michael Kane & Wei Wei & Denise Esserman & Daniel Zelterman
September 2022, Volume 33, Issue 6
- e2733 Covariance structure assessment in multi‐level models for the analysis of forests rainfall interception data using repeated measures
by Efrain Velasco‐Bautista & Martin Enrique Romero‐Sanchez & Eulogio Flores‐Ayala - e2742 Practical strategies for generalized extreme value‐based regression models for extremes
by Daniela Castro‐Camilo & Raphaël Huser & Håvard Rue - e2743 Reconstruction of past human land use from pollen data and anthropogenic land cover changes
by Behnaz Pirzamanbein & Johan Lindström - e2744 A flexible extended generalized Pareto distribution for tail estimation
by Philémon Gamet & Jonathan Jalbert - e2747 Nonparametric estimation of variable productivity Hawkes processes
by Frederic Paik Schoenberg
August 2022, Volume 33, Issue 5
- e2726 Improving piecewise linear snow density models through hierarchical spatial and orthogonal functional smoothing
by Philip A. White & Durban G. Keeler & Daniel Sheanshang & Summer Rupper - e2727 Mitigating spatial confounding by explicitly correlating Gaussian random fields
by Isa Marques & Thomas Kneib & Nadja Klein - e2728 Continuous model averaging for benchmark dose analysis: Averaging over distributional forms
by Matthew W. Wheeler & Jose Cortiñas Abrahantes & Marc Aerts & Jeffery S. Gift & Jerry Allen Davis - e2729 Two‐phase adaptive cluster sampling with circular field plots
by Wilmer Prentius & Anton Grafström - e2730 Normalization methods for spatio‐temporal analysis of environmental performance: Revisiting the Min–Max method
by Matteo Mazziotta & Adriano Pareto
June 2022, Volume 33, Issue 4
- e2713 Spatial matrix completion for spatially misaligned and high‐dimensional air pollution data
by Phuong T. Vu & Adam A. Szpiro & Noah Simon - e2714 Recognizing a spatial extreme dependence structure: A deep learning approach
by Manaf Ahmed & Véronique Maume‐Deschamps & Pierre Ribereau - e2719 Quantile based modeling of diurnal temperature range with the five‐parameter lambda distribution
by Silius M. Vandeskog & Thordis L. Thorarinsdottir & Ingelin Steinsland & Finn Lindgren - e2723 A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown
by Guido Fioravanti & Michela Cameletti & Sara Martino & Giorgio Cattani & Enrico Pisoni - e2724 A notable Gamma‐Lindley first‐order autoregressive process: An application to hydrological data
by Alice B. V. Mello & Maria C. S. Lima & Abraão D. C. Nascimento
May 2022, Volume 33, Issue 3
- e2706 A combined estimate of global temperature
by Peter F. Craigmile & Peter Guttorp - e2712 A nonstationary and non‐Gaussian moving average model for solar irradiance
by Wenqi Zhang & William Kleiber & Bri‐Mathias Hodge & Barry Mather - e2716 Statistical analysis of multi‐day solar irradiance using a threshold time series model
by Carolina Euán & Ying Sun & Brian J. Reich - e2717 Discussion on “A combined estimate of global temperature”
by Fabio Madonna - e2718 Discussion on “A combined estimate of global temperature”
by Andrew Poppick & Michael L. Stein - e2720 Discussion on “A combined estimate of global temperature”
by Alexandra M. Schmidt & Marco A. Rodríguez - e2721 Discussion on “A combined estimate of global temperature”
by Karen A. McKinnon - e2722 Discussion on “A combined estimate of global temperature”
by Peter W. Thorne - e2725 Rejoinder to the discussion on “A combined estimate of global temperature”
by Peter F. Craigmile & Peter Guttorp
March 2022, Volume 33, Issue 2
- e2707 Managing air quality: Predicting exceedances of legal limits for PM10 and O3 concentration using machine learning methods
by Maryna Krylova & Yarema Okhrin - e2708 Modeling cycles and interdependence in irregularly sampled geophysical time series
by Granville Tunnicliffe Wilson & John Haywood & Lynda Petherick - e2709 Impact of the mesoscale structure of a bipartite ecological interaction network on its robustness through a probabilistic modeling
by Saint‐Clair Chabert‐Liddell & Pierre Barbillon & Sophie Donnet - e2710 Scalable multiple changepoint detection for functional data sequences
by Trevor Harris & Bo Li & J. Derek Tucker - e2711 Generalization of the power‐law rating curve using hydrodynamic theory and Bayesian hierarchical modeling
by Birgir Hrafnkelsson & Helgi Sigurdarson & Sölvi Rögnvaldsson & Axel Örn Jansson & Rafael Daníel Vias & Sigurdur M. Gardarsson
February 2022, Volume 33, Issue 1
- e2699 A Dirichlet process model for change‐point detection with multivariate bioclimatic data
by Gianluca Mastrantonio & Giovanna Jona Lasinio & Alessio Pollice & Lorenzo Teodonio & Giulia Capotorti - e2701 Random fields on the hypertorus: Covariance modeling and applications
by Emilio Porcu & Philip A. White - e2702 Using an autonomous underwater vehicle with onboard stochastic advection‐diffusion models to map excursion sets of environmental variables
by Karine Hagesæther Foss & Gunhild Elisabeth Berget & Jo Eidsvik - e2703 A projection‐based Laplace approximation for spatial latent variable models
by Jaewoo Park & Sangwan Lee - e2705 Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross‐sectional resampling
by Miryam S. Merk & Philipp Otto
December 2021, Volume 32, Issue 8
- e2695 An evolutionary Monte Carlo method for the analysis of turbidity high‐frequency time series through Markov switching autoregressive models
by Luigi Spezia & Andy Vinten & Roberta Paroli & Marc Stutter - e2696 Spatial cluster detection with threshold quantile regression
by Junho Lee & Ying Sun & Huixia Judy Wang - e2697 A self‐exciting marked point process model for drought analysis
by Xiaoting Li & Christian Genest & Jonathan Jalbert - e2698 A hierarchical integrative group least absolute shrinkage and selection operator for analyzing environmental mixtures
by Jonathan Boss & Alexander Rix & Yin‐Hsiu Chen & Naveen N. Narisetty & Zhenke Wu & Kelly K. Ferguson & Thomas F. McElrath & John D. Meeker & Bhramar Mukherjee - e2700 A cyclostationary model for temporal forecasting and simulation of solar global horizontal irradiance
by Soumya Das & Marc G. Genton & Yasser M. Alshehri & Georgiy L. Stenchikov - e2704 A parametric model for distributions with flexible behaviour in both tails
by Michael L. Stein
November 2021, Volume 32, Issue 7
- e2680 On testing for the equality of autocovariance in time series
by Daniel Cirkovic & Thomas J. Fisher - e2681 Spatiotemporal clustering using Gaussian processes embedded in a mixture model
by Jarno Vanhatalo & Scott D. Foster & Geoffrey R. Hosack - e2682 Bayesian variable selection for high‐dimensional rank data
by Can Cui & Susheela P. Singh & Ana‐Maria Staicu & Brian J. Reich - e2684 Generalized least‐squares in dimension expansion method for nonstationary processes
by Shanshan Qin & Bin Sun & Yuehua Wu & Yuejiao Fu - e2694 Heterogeneity pursuit for spatial point pattern with application to tree locations: A Bayesian semiparametric recourse
by Jieying Jiao & Guanyu Hu & Jun Yan
September 2021, Volume 32, Issue 6
- e2665 On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi‐annual harmonics
by Joshua S. North & Erin M. Schliep & Christopher K. Wikle - e2678 Truncated generalized extreme value distribution‐based ensemble model output statistics model for calibration of wind speed ensemble forecasts
by Sándor Baran & Patrícia Szokol & Marianna Szabó - e2679 Bayesian estimation of heterogeneous environments from animal movement data
by Svetlana V. Tishkovskaya & Paul G. Blackwell - e2683 Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models
by Jenni Niku & Francis K. C. Hui & Sara Taskinen & David I. Warton - e2685 Modeling the duration and size of wildfires using joint mixture models
by Dexen D. Z. Xi & Charmaine B. Dean & Stephen W. Taylor
August 2021, Volume 32, Issue 5
- e2669 Identifying meteorological drivers of PM2.5 levels via a Bayesian spatial quantile regression
by Stella W. Self & Christopher S. McMahan & Brook T. Russell - e2670 Flexible nonstationary spatiotemporal modeling of high‐frequency monitoring data
by Christopher J. Geoga & Mihai Anitescu & Michael L. Stein - e2671 Spatial deformation for nonstationary extremal dependence
by Jordan Richards & Jennifer L. Wadsworth - e2676 Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers
by Mehdi Jabbari Nooghabi - e2677 Benchmark dose risk analysis with mixed‐factor quantal data in environmental risk assessment
by Maria A. Sans‐Fuentes & Walter W. Piegorsch
June 2021, Volume 32, Issue 4
- e2667 Modeling nonstationary extremes of storm severity: Comparing parametric and semiparametric inference
by Evandro Konzen & Cláudia Neves & Philip Jonathan - e2668 Causal inference for quantile treatment effects
by Shuo Sun & Erica E. M. Moodie & Johanna G. Nešlehová - e2672 A unified skew‐normal geostatistical factor model
by Marco Minozzo & Luca Bagnato - e2674 Spatial dependence of extreme seas in the North East Atlantic from satellite altimeter measurements
by R. Shooter & E. Ross & A. Ribal & I. R. Young & P. Jonathan - e2675 High‐dimensional multivariate geostatistics: A Bayesian matrix‐normal approach
by Lu Zhang & Sudipto Banerjee & Andrew O. Finley
May 2021, Volume 32, Issue 3
- e2660 Data fusion with Gaussian processes for estimation of environmental hazard events
by Xiaoyu Xiong & Benjamin D. Youngman & Theodoros Economou - e2661 Modeling short‐ranged dependence in block extrema with application to polar temperature data
by Brook T. Russell & Whitney K. Huang - e2662 Spatial hierarchical modeling of threshold exceedances using rate mixtures
by Rishikesh Yadav & Raphaël Huser & Thomas Opitz - e2663 Likelihood‐based inference for spatiotemporal data with censored and missing responses
by Katherine A. L. Valeriano & Victor H. Lachos & Marcos O. Prates & Larissa A. Matos - e2664 Fast grid search and bootstrap‐based inference for continuous two‐phase polynomial regression models
by Hyunju Son & Youyi Fong
March 2021, Volume 32, Issue 2
- e2655 A smoothing spline model for multimodal and skewed circular responses: Applications in meteorology and oceanography
by Fatemeh Hassanzadeh - e2656 Simultaneous autoregressive models for spatial extremes
by Miranda J. Fix & Daniel S. Cooley & Emeric Thibaud - e2657 A spatiotemporal model for multivariate occupancy data
by Staci A. Hepler & Robert J. Erhardt - e2658 A parametric model for distributions with flexible behavior in both tails
by Michael L. Stein - e2673 Effects of corona virus disease‐19 control measures on air quality in North China
by Xiangyu Zheng & Bin Guo & Jing He & Song Xi Chen
February 2021, Volume 32, Issue 1
- e2641 Robust functional multivariate analysis of variance with environmental applications
by Zhuo Qu & Wenlin Dai & Marc G. Genton - e2646 Sequential tests of causality between environmental time series: With application to the global warming theory
by Carlo Grillenzoni & Elisa Carraro - e2648 A spatio‐temporal model for the analysis and prediction of fine particulate matter concentration in Beijing
by Yating Wan & Minya Xu & Hui Huang & Song Xi Chen - e2653 A spatial capture–recapture model with attractions between individuals
by Paul McLaughlin & Haim Bar - e2654 Adjusting a finite population block kriging estimator for imperfect detection
by Matt Higham & Jay Ver Hoef & Lisa Madsen & Andy Aderman
December 2020, Volume 31, Issue 8
- e2631 Detecting British Columbia coastal rainfall patterns by clustering Gaussian processes
by F. Paton & P.D. McNicholas - e2642 Bayesian nonparametric monotone regression
by Ander Wilson & Jessica Tryner & Christian L'Orange & John Volckens - e2643 Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution
by Duncan Lee & Chris Robertson & Colin Ramsay & Kate Pyper - e2644 A joint Bayesian space–time model to integrate spatially misaligned air pollution data in R‐INLA
by C. Forlani & S. Bhatt & M. Cameletti & E. Krainski & M. Blangiardo - e2645 Functional estimation of diversity profiles
by Francesca Fortuna & Stefano Antonio Gattone & Tonio Di Battista
November 2020, Volume 31, Issue 7
- e2627 Space‐time autoregressive estimation and prediction with missing data based on Kalman filtering
by Leonardo Padilla & Bernado Lagos‐Álvarez & Jorge Mateu & Emilio Porcu - e2628 A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Felipe Tagle & Marc G. Genton & Andrew Yip & Suleiman Mostamandi & Georgiy Stenchikov & Stefano Castruccio - e2629 Ensemble forecasting of the Zika space‐time spread with topological data analysis
by Marwah Soliman & Vyacheslav Lyubchich & Yulia R. Gel - e2630 An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data
by Marc Aerts & Matthew W. Wheeler & José Cortiñas Abrahantes - e2632 On modeling positive continuous data with spatiotemporal dependence
by Moreno Bevilacqua & Christian Caamaño‐Carrillo & Carlo Gaetan - e2647 Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Adelchi Azzalini - e2649 Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Andrew Zammit‐Mangion - e2650 Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Sándor Baran - e2651 Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Emilio Porcu & Jonas Rysgaard & Valerie Eveloy - e2659 Rejoinder to the discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources
by Felipe Tagle & Marc G. Genton & Andrew Yip & Suleiman Mostamandi & Georgiy Stenchikov & Stefano Castruccio
September 2020, Volume 31, Issue 6
- e2615 Bayesian estimation and model selection of a multivariate smooth transition autoregressive model
by Glen Livingston Jr & Darfiana Nur - e2618 A lattice and random intermediate point sampling design for animal movement
by Elizabeth Eisenhauer & Ephraim Hanks - e2623 Incorporating covariate information in the covariance structure of misaligned spatial data
by Esmail Yarali & Firoozeh Rivaz - e2625 A sample coordination method to monitor totals of environmental variables
by Xin Zhao & Anton Grafström - e2652 Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation
by Ashton Wiens & Douglas Nychka & William Kleiber
August 2020, Volume 31, Issue 5
- e2616 Predicting extreme surges from sparse data using a copula‐based hierarchical Bayesian spatial model
by N. Beck & C. Genest & J. Jalbert & M. Mailhot - e2619 Modeling the duration and size of extended attack wildfires as dependent outcomes
by Dexen DZ. Xi & C.B. Dean & Stephen W. Taylor - e2621 Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland
by John O'Sullivan & Conor Sweeney & Andrew C. Parnell - e2624 Flexible covariate representations for extremes
by E. Zanini & E. Eastoe & M. J. Jones & D. Randell & P. Jonathan - e2626 Heatwave duration: Characterizations using probabilistic inference
by Sohini Raha & Sujit K. Ghosh
June 2020, Volume 31, Issue 4
- e2608 Bayesian spatial analysis of hardwood tree counts in forests via MCMC
by Reihaneh Entezari & Patrick E. Brown & Jeffrey S. Rosenthal - e2609 Modeling sea‐level processes on the U.S. Atlantic Coast
by Candace Berrett & William F. Christensen & Stephan R. Sain & Nathan Sandholtz & David W. Coats & Claudia Tebaldi & Hedibert F. Lopes - e2610 Spatiotemporal reconstructions of global CO2‐fluxes using Gaussian Markov random fields
by Unn Dahlén & Johan Lindström & Marko Scholze - e2611 A permutation approach to the analysis of spatiotemporal geochemical data in the presence of heteroscedasticity
by Veronika Římalová & Alessandra Menafoglio & Alessia Pini & Vilém Pechanec & Eva Fišerová - e2613 Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images
by Victor Freguglia & Nancy L. Garcia & Juliano L. Bicas - e2614 Probabilistic predictive principal component analysis for spatially misaligned and high‐dimensional air pollution data with missing observations
by Phuong T. Vu & Timothy V. Larson & Adam A. Szpiro
May 2020, Volume 31, Issue 3
- e2602 A multivariate spatial skew‐t process for joint modeling of extreme precipitation indexes
by Arnab Hazra & Brian J. Reich & Ana‐Maria Staicu - e2603 Estimating population size with imperfect detection using a parametric bootstrap
by Lisa Madsen & Dan Dalthorp & Manuela Maria Patrizia Huso & Andy Aderman - e2604 Nonlinear reaction–diffusion process models improve inference for population dynamics
by Xinyi Lu & Perry J. Williams & Mevin B. Hooten & James A. Powell & Jamie N. Womble & Michael R. Bower - e2605 Space–time trends and dependence of precipitation extremes in North‐Western Germany
by R. Cabral & A. Ferreira & P. Friederichs - e2606 Bayesian inference for finite populations under spatial process settings
by Alec M. Chan‐Golston & Sudipto Banerjee & Mark S. Handcock - e2607 Goodness‐of‐fit tests for βARMA hydrological time series modeling
by Vinícius T. Scher & Francisco Cribari‐Neto & Guilherme Pumi & Fábio M. Bayer
March 2020, Volume 31, Issue 2
- e2572 Model‐based clustering for noisy longitudinal circular data, with application to animal movement
by M. Ranalli & A. Maruotti - e2578 Spatial cluster detection of regression coefficients in a mixed‐effects model
by Junho Lee & Ying Sun & Howard H. Chang - e2582 Flexible semiparametric generalized Pareto modeling of the entire range of rainfall amount
by P. Tencaliec & A.‐C. Favre & P. Naveau & C. Prieur & G. Nicolet - e2594 Spatio‐Temporal data fusion for massive sea surface temperature data from MODIS and AMSR‐E instruments
by Pulong Ma & Emily L. Kang - e2595 Investigating the association between late spring Gulf of Mexico sea surface temperatures and U.S. Gulf Coast precipitation extremes with focus on Hurricane Harvey
by Brook T. Russell & Mark D. Risser & Richard L. Smith & Kenneth E. Kunkel - e2596 Bayesian time‐varying quantile regression to extremes
by Fernando Ferraz Do Nascimento & Marcelo Bourguignon - e2599 Spatio‐temporal classification in point patterns under the presence of clutter
by Marianna Siino & Francisco J. Rodríguez‐Cortés & Jorge Mateu & Giada Adelfio
February 2020, Volume 31, Issue 1
- e2568 Considering long‐memory when testing for changepoints in surface temperature: A classification approach based on the time‐varying spectrum
by Claudie Beaulieu & Rebecca Killick & David Ireland & Ben Norwood - e2570 Changepoint analysis of Klementinum temperature series
by D. Jarušková & J. Antoch - e2576 A nonparametric approach to detecting changes in variance in locally stationary time series
by J.‐L. Chapman & I. A. Eckley & R. Killick - e2577 A conversation with Ian MacNeill
by Venkata K. Jandhyala & Elena N. Naumova - e2580 Trend assessment for daily snow depths with changepoint considerations
by J. Lee & R. Lund & J. Woody & Y. Xu - e2591 A data‐driven approach to detecting change points in linear regression models
by Vyacheslav Lyubchich & Tatiana V. Lebedeva & Jeremy M. Testa - e2593 Multiple change‐point models for time series
by I.B. MacNeill & V.K. Jandhyala & A. Kaul & S.B. Fotopoulos - e2612 Harnessing the power of topological data analysis to detect change points
by Umar Islambekov & Monisha Yuvaraj & Yulia R. Gel - e2617 Structural break analysis for spectrum and trace of covariance operators
by A. Aue & G. Rice & O. Sönmez - e2620 Change‐point methods for environmental monitoring and assessment
by Venkata K. Jandhyala & Yulia Gel
December 2019, Volume 30, Issue 8
- e2569 An additive approximate Gaussian process model for large spatio‐temporal data
by Pulong Ma & Bledar A. Konomi & Emily L. Kang - e2571 Computationally efficient nonstationary nearest‐neighbor Gaussian process models using data‐driven techniques
by B. A. Konomi & A. A. Hanandeh & P. Ma & E. L. Kang - e2573 Error in estimating area‐level air pollution exposures for epidemiology
by Joshua P. Keller & Roger D. Peng - e2575 Model‐based inference of conditional extreme value distributions with hydrological applications
by R. P. Towe & J. A. Tawn & R. Lamb & C. G. Sherlock - e2579 A model for Antarctic surface mass balance and ice core site selection
by Philip A. White & C. Shane Reese & William F. Christensen & Summer Rupper - e2598 Comments on Schoenberg et al. (2003)
by Hamid Ghorbani - e2601 Rejoinder to “Comments on Schoenberg et al. (2003)” by Hamid Ghorbani
by Frederic Paik Schoenberg
November 2019, Volume 30, Issue 7
- e2561 Age‐specific distributed lag models for heat ‐ related mortality
by M. J. Heaton & C. R. Olenick & O. Wilhelmi - e2574 Bayesian spatiotemporal modeling for estimating short‐term exposure to air pollution in Santiago de Chile
by O. Nicolis & M. Díaz & S. K. Sahu & J. C. Marín - e2581 Nonstationary spatiotemporal Bayesian data fusion for pollutants in the near‐road environment
by O. Gilani & V. J. Berrocal & S. A. Batterman