Environmetrics

Papers
(The median citation count of Environmetrics is 1. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-10-01 to 2025-10-01.)
ArticleCitations
78
Modeling cycles and interdependence in irregularly sampled geophysical time series23
Scalable multiple changepoint detection for functional data sequences21
Rejoinder to the discussion on “A combined estimate of global temperature”16
Continuous model averaging for benchmark dose analysis: Averaging over distributional forms16
Catalysing virtual collaboration: The experience of the remote TIES working groups12
Nonlinear prediction of functional time series11
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2023 Editorial Collaborators10
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An illustration of model agnostic explainability methods applied to environmental data9
Principal component analysis for river network data: Use of spatiotemporal correlation and heterogeneous covariance structure9
Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes9
Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objects8
Issue Information8
Global sensitivity and domain‐selective testing for functional‐valued responses: An application to climate economy models8
Issue Information8
Issue Information8
Analyzing Inter‐Hemispheric Climate Change Asymmetries With a Cointegrated Vector Autoregression8
Clustering of bivariate satellite time series: A quantile approach8
Assessing predictability of environmental time series with statistical and machine learning models7
A Bayesian framework for studying climate anomalies and social conflicts7
Uncertainty: Nothing is more certain7
Discussion on “A combined estimate of global temperature”7
Issue Information7
Gradient‐Boosted Generalized Linear Models for Conditional Vine Copulas7
A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields7
Statistical Inference for Natural Resources and Biodiversity7
A double fixed rank kriging approach to spatial regression models with covariate measurement error6
Discussion on “A combined estimate of global temperature”6
Pesticide concentration monitoring: Investigating spatio‐temporal patterns in left censored data6
Record events attribution in climate studies5
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Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada5
Issue Information5
Calibrated forecasts of quasi‐periodic climate processes with deep echo state networks and penalized quantile regression5
Stochastic tropical cyclone precipitation field generation5
Emulation of greenhouse‐gas sensitivities using variational autoencoders5
Modeling Disease Dynamics From Spatially Explicit Capture‐Recapture Data5
Structural equation models for simultaneous modeling of air pollutants5
Exact optimisation of spatiotemporal monitoring networks by p‐splines with applications in groundwater assessment4
Assessing the ability of adaptive designs to capture trends in hard coral cover4
Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires4
Practical strategies for generalized extreme value‐based regression models for extremes4
Conjugate sparse plus low rank models for efficient Bayesian interpolation of large spatial data4
A Multivariate Space‐Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt. Pinatubo Eruption4
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Estimation of change with partially overlapping and spatially balanced samples4
Issue Information4
Correction to “Estimation of Impact Ranges for Functional Valued Predictors”4
Covariance structure assessment in multi‐level models for the analysis of forests rainfall interception data using repeated measures4
Comparing emulation methods for a high‐resolution storm surge model4
Semiparametric Approaches for Mitigating Spatial Confounding in Large Environmental Epidemiology Cohort Studies4
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach4
CO2has significant implications for hourly ambient temperature: Evidence from Hawaii4
REDS: Random ensemble deep spatial prediction4
Spike and Slab Regression for Nonstationary Gaussian Linear Mixed Effects Modeling of Rapid Disease Progression4
Categorical data analysis using discretization of continuous variables to investigate associations in marine ecosystems4
Comparative Analysis of Bootstrap Techniques for Confidence Interval Estimation in Spatial Covariance Parameters With Large Spatial Data4
Long memory conditional random fields on regular lattices3
Multivariate nearest‐neighbors Gaussian processes with random covariance matrices3
The scope of the Kalman filter for spatio‐temporal applications in environmental science3
Detection of anomalous radioxenon concentrations: A distribution‐free approach3
Intersection between environmental data science and the R community in Latin America3
Joint species distribution modeling with competition for space3
“Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”3
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Generalized gamma ARMA process for synthetic aperture radar amplitude and intensity data3
New generalized extreme value distribution with applications to extreme temperature data3
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The role of data science in environmental digital twins: In praise of the arrows3
Spatiotemporal Causal Inference With Mechanistic Ecological Models: Evaluating Targeted Culling on Chronic Wasting Disease Dynamics in Cervids3
Generalization of the power‐law rating curve using hydrodynamic theory and Bayesian hierarchical modeling3
Using Expected Improvement of Gradients for Robotic Exploration of Ocean Salinity Fronts3
Environmental data science: Part 13
Modeling Anisotropy and Non‐Stationarity Through Physics‐Informed Spatial Regression3
Framing data science, analytics and statistics around the digital earth concept3
3
Regression methods for the appearances of extremes in climate data2
Total least squares bias in climate fingerprinting regressions with heterogeneous noise variances and correlated explanatory variables2
Issue Information2
A spatially‐weighted AMH copula‐based dissimilarity measure for clustering variables: An application to urban thermal efficiency2
Approximation of Bayesian Hawkes process with inlabru2
Issue Information2
A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown2
Estimating Extreme Wave Surges in the Presence of Missing Data2
Pointwise data depth for univariate and multivariate functional outlier detection2
Bayesian benchmark dose risk assessment with mixed‐factor quantal data2
P‐min‐Stable Regression Models for Time Series With Extreme Values of Limited Range2
A notable Gamma‐Lindley first‐order autoregressive process: An application to hydrological data2
Does Wind Affect the Orientation of Vegetation Stripes? A Copula‐Based Mixture Model for Axial and Circular Data2
On the impact of spatial covariance matrix ordering on tile low‐rank estimation of Matérn parameters2
Animal Trajectory Imputation and Uncertainty Quantification via Deep Learning2
Modeling temporally misaligned data across space: The case of total pollen concentration in Toronto2
A zero‐inflated Poisson spatial model with misreporting for wildfire occurrences in southern Italian municipalities2
Functional zoning of biodiversity profiles2
Families of complex‐valued covariance models through integration2
Computational Benchmark Study in Spatio‐Temporal Statistics With a Hands‐On Guide to Optimise R2
Discussion on “Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”2
Data science and climate risk analytics1
Estimation of Impact Ranges for Functional Valued Predictors1
A Partially Varying‐Coefficient Model With Skew‐T Random Errors for Environmental Data Modeling1
New Parametric Approach for Modeling Hydrological Data: An Alternative to the Beta, Kumaraswamy, and Simplex Models1
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On the identifiability of the trinomial model for mark‐recapture‐recovery studies1
How to find the best sampling design: A new measure of spatial balance1
Semiparametric Copula‐Based Confidence Intervals on Level Curves for the Evaluation of the Risk Level Associated to Bivariate Events1
Issue Information1
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Effects of Climate Change on House Prices in Outdoor Tourism Destinations: A Case Study of Southwestern Colorado1
Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes1
Novel Approach for Hierarchical Family Selection of an Ambient Air Pollutant Mixture With Application to Childhood Asthma1
On Tail Structural Change in U.S. Climate Data1
Front Cover Image, Volume 34, Number 1, February 20231
Issue Information1
Does the Quality of Political Institutions Matter for the Effectiveness of Environmental Taxes? An Empirical Analysis on CO2 Emissions1
A nonstationary and non‐Gaussian moving average model for solar irradiance1
2021 Editorial Collaborators1
Issue Information1
Discussion on Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models1
Shooting for abundance: Comparing integrated multi‐sampling models for camera trap and hair trap data1
Skew Gaussian Markov Random Fields Under Decomposable Graphs1
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A Non‐Parametric Estimation Method of the Population Size in Capture‐Recapture Experiments With Right Censored Data1
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Multistage hierarchical capture–recapture models1
Fuzzy Clustering of Circular Time Series With Applications to Wind Data1
Characterizing Asymptotic Dependence between a Satellite Precipitation Product and Station Data in the Northern US Rocky Mountains via the Tail Dependence Regression Framework With a Gibbs 1
Adaptive Now‐ and Forecasting of Global Temperatures Under Smooth Structural Changes1
Mitigating spatial confounding by explicitly correlating Gaussian random fields1
On the selection of an interpolation method with an application to the Fire Weather Index in Ontario, Canada1
Issue Information1
Statistical evaluation of a long‐memory process using the generalized entropic value‐at‐risk1
A Separable Bootstrap Variance Estimation Algorithm for Hierarchical Model‐Based Inference of Forest Aboveground Biomass Using Data From NASA's GEDI and Landsat Missions1
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Fast parameter estimation of generalized extreme value distribution using neural networks1
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