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 2021-08-01 to 2025-08-01.)
ArticleCitations
65
Modeling cycles and interdependence in irregularly sampled geophysical time series21
A Dirichlet process model for change‐point detection with multivariate bioclimatic data20
Rejoinder to the discussion on “A combined estimate of global temperature”15
Scalable multiple changepoint detection for functional data sequences15
A parametric model for distributions with flexible behaviour in both tails11
Nonlinear prediction of functional time series10
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Continuous model averaging for benchmark dose analysis: Averaging over distributional forms10
Catalysing virtual collaboration: The experience of the remote TIES working groups10
2023 Editorial Collaborators9
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Principal component analysis for river network data: Use of spatiotemporal correlation and heterogeneous covariance structure8
Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes8
A projection‐based Laplace approximation for spatial latent variable models7
Issue Information7
A Bayesian framework for studying climate anomalies and social conflicts7
Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objects7
Clustering of bivariate satellite time series: A quantile approach7
Issue Information7
A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields7
Uncertainty: Nothing is more certain7
An illustration of model agnostic explainability methods applied to environmental data7
Issue Information7
Discussion on “A combined estimate of global temperature”7
Gradient‐Boosted Generalized Linear Models for Conditional Vine Copulas7
A double fixed rank kriging approach to spatial regression models with covariate measurement error6
Assessing predictability of environmental time series with statistical and machine learning models6
Issue Information6
Discussion on “A combined estimate of global temperature”6
Pesticide concentration monitoring: Investigating spatio‐temporal patterns in left censored data6
Global sensitivity and domain‐selective testing for functional‐valued responses: An application to climate economy models6
Record events attribution in climate studies5
Modeling Disease Dynamics From Spatially Explicit Capture‐Recapture Data5
Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada5
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Emulation of greenhouse‐gas sensitivities using variational autoencoders5
Statistical Inference for Natural Resources and Biodiversity5
Stochastic tropical cyclone precipitation field generation5
Calibrated forecasts of quasi‐periodic climate processes with deep echo state networks and penalized quantile regression5
Issue Information5
REDS: Random ensemble deep spatial prediction5
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach4
Assessing the ability of adaptive designs to capture trends in hard coral cover4
CO2has significant implications for hourly ambient temperature: Evidence from Hawaii4
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Conjugate sparse plus low rank models for efficient Bayesian interpolation of large spatial data4
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Practical strategies for generalized extreme value‐based regression models for extremes4
Issue Information4
Exact optimisation of spatiotemporal monitoring networks by p‐splines with applications in groundwater assessment4
Semiparametric Approaches for Mitigating Spatial Confounding in Large Environmental Epidemiology Cohort Studies4
Comparing emulation methods for a high‐resolution storm surge model4
Using an autonomous underwater vehicle with onboard stochastic advection‐diffusion models to map excursion sets of environmental variables4
Estimation of change with partially overlapping and spatially balanced samples4
Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires4
Structural equation models for simultaneous modeling of air pollutants4
Spike and Slab Regression for Nonstationary Gaussian Linear Mixed Effects Modeling of Rapid Disease Progression4
Issue Information4
Categorical data analysis using discretization of continuous variables to investigate associations in marine ecosystems4
The scope of the Kalman filter for spatio‐temporal applications in environmental science3
Comparative Analysis of Bootstrap Techniques for Confidence Interval Estimation in Spatial Covariance Parameters With Large Spatial Data3
Generalization of the power‐law rating curve using hydrodynamic theory and Bayesian hierarchical modeling3
Joint species distribution modeling with competition for space3
“Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”3
New generalized extreme value distribution with applications to extreme temperature data3
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Generalized gamma ARMA process for synthetic aperture radar amplitude and intensity data3
Modeling Anisotropy and Non‐Stationarity Through Physics‐Informed Spatial Regression3
Framing data science, analytics and statistics around the digital earth concept3
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Multivariate nearest‐neighbors Gaussian processes with random covariance matrices3
Intersection between environmental data science and the R community in Latin America3
Environmental data science: Part 13
Detection of anomalous radioxenon concentrations: A distribution‐free approach3
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The role of data science in environmental digital twins: In praise of the arrows3
Long memory conditional random fields on regular lattices3
Covariance structure assessment in multi‐level models for the analysis of forests rainfall interception data using repeated measures3
Modeling temporally misaligned data across space: The case of total pollen concentration in Toronto2
2
Issue Information2
Animal Trajectory Imputation and Uncertainty Quantification via Deep Learning2
Total least squares bias in climate fingerprinting regressions with heterogeneous noise variances and correlated explanatory variables2
Approximation of Bayesian Hawkes process with inlabru2
Regression methods for the appearances of extremes in climate data2
Spatiotemporal Causal Inference With Mechanistic Ecological Models: Evaluating Targeted Culling on Chronic Wasting Disease Dynamics in Cervids2
A combined estimate of global temperature2
Computational Benchmark Study in Spatio‐Temporal Statistics With a Hands‐On Guide to Optimise R2
A notable Gamma‐Lindley first‐order autoregressive process: An application to hydrological data2
A spatially‐weighted AMH copula‐based dissimilarity measure for clustering variables: An application to urban thermal efficiency2
On the impact of spatial covariance matrix ordering on tile low‐rank estimation of Matérn parameters2
A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown2
Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross‐sectional resampling2
Discussion on “Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models”2
Families of complex‐valued covariance models through integration2
Issue Information2
Does Wind Affect the Orientation of Vegetation Stripes? A Copula‐Based Mixture Model for Axial and Circular Data2
Random fields on the hypertorus: Covariance modeling and applications1
P‐min‐Stable Regression Models for Time Series With Extreme Values of Limited Range1
A zero‐inflated Poisson spatial model with misreporting for wildfire occurrences in southern Italian municipalities1
Functional zoning of biodiversity profiles1
Shooting for abundance: Comparing integrated multi‐sampling models for camera trap and hair trap data1
Issue Information1
A Separable Bootstrap Variance Estimation Algorithm for Hierarchical Model‐Based Inference of Forest Aboveground Biomass Using Data From NASA's GEDI and Landsat Missions1
Issue Information1
1
How to find the best sampling design: A new measure of spatial balance1
Front Cover Image, Volume 34, Number 1, February 20231
Fast parameter estimation of generalized extreme value distribution using neural networks1
Issue Information1
On Tail Structural Change in U.S. Climate Data1
Pointwise data depth for univariate and multivariate functional outlier detection1
Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes1
On the selection of an interpolation method with an application to the Fire Weather Index in Ontario, Canada1
On the identifiability of the trinomial model for mark‐recapture‐recovery studies1
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Discussion on Assessing Predictability of Environmental Time Series With Statistical and Machine Learning Models1
2021 Editorial Collaborators1
Issue Information1
A Non‐Parametric Estimation Method of the Population Size in Capture‐Recapture Experiments With Right Censored Data1
Estimation of Impact Ranges for Functional Valued Predictors1
Multistage hierarchical capture–recapture models1
Data science and climate risk analytics1
Issue Information1
1
Bayesian benchmark dose risk assessment with mixed‐factor quantal data1
1
Novel Approach for Hierarchical Family Selection of an Ambient Air Pollutant Mixture With Application to Childhood Asthma1
Statistical evaluation of a long‐memory process using the generalized entropic value‐at‐risk1
A nonstationary and non‐Gaussian moving average model for solar irradiance1
Mitigating spatial confounding by explicitly correlating Gaussian random fields1
Semiparametric Copula‐Based Confidence Intervals on Level Curves for the Evaluation of the Risk Level Associated to Bivariate Events1
Effects of Climate Change on House Prices in Outdoor Tourism Destinations: A Case Study of Southwestern Colorado1
Issue Information1
1
A Partially Varying‐Coefficient Model With Skew‐T Random Errors for Environmental Data Modeling1
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