The following pages link to geoR (Q16662):
Displaying 40 items.
- A comparison of spatial predictors when datasets could be very large (Q311779) (← links)
- Effective sample size for line transect sampling models with an application to marine macroalgae (Q321444) (← links)
- Combining robustness with efficiency in the estimation of the variogram (Q539033) (← links)
- Spatial variability in slash linear modeling with finite second moment (Q725261) (← links)
- Recent developments in complex and spatially correlated functional data (Q783297) (← links)
- A stochastic neighborhood conditional autoregressive model for spatial data (Q961743) (← links)
- Data-driven neighborhood selection of a Gaussian field (Q962389) (← links)
- Geostatistical computing of acoustic maps in the presence of barriers (Q969984) (← links)
- Mixed effects models and extensions in ecology with R (Q999158) (← links)
- Fast kriging of large data sets with Gaussian Markov random fields (Q1023566) (← links)
- Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package (Q1621383) (← links)
- Prediction intervals for integrals of Gaussian random fields (Q1623768) (← links)
- Modeling spatial anisotropy via regression with partial differential regularization (Q1661326) (← links)
- Simulated variogram-based error inspection of manufactured parts (Q1757251) (← links)
- Semiparametric regression during 2003--2007 (Q1952023) (← links)
- Spatiotemporal satellite data imputation using sparse functional data analysis (Q2080746) (← links)
- Hybrid MLP-IDW approach based on nearest neighbor for spatial prediction (Q2095726) (← links)
- A computational validation for nonparametric assessment of spatial trends (Q2135946) (← links)
- A goodness-of-fit test for regression models with spatially correlated errors (Q2220799) (← links)
- Modeling space-time dynamics of aerosols using satellite data and atmospheric transport model output (Q2261039) (← links)
- A conversation with Peter Diggle (Q2292399) (← links)
- Mantel test for spatial functional data. An application to infiltration curves (Q2316717) (← links)
- Development and evaluation of geostatistical methods for non-Euclidean-based spatial covariance matrices (Q2323497) (← links)
- Comparing and selecting spatial predictors using local criteria (Q2348712) (← links)
- On the use of non-Euclidean distance measures in geostatistics (Q2454621) (← links)
- A comparison of approaches for valid variogram achievement (Q2488430) (← links)
- A note on the choice and the estimation of Kriging models for the analysis of deterministic computer experiments (Q3077457) (← links)
- (Q3096108) (← links)
- Spatial misalignment in time series studies of air pollution and health data (Q3303635) (← links)
- Comparison of Kriging and artificial neural network models for the prediction of spatial data (Q3390484) (← links)
- A Kernel Variogram Estimator for Clustered Data (Q3608250) (← links)
- (Q4450531) (← links)
- Model-based Geostatistics for Global Public Health (Q4631630) (← links)
- Practical Bayesian modeling and inference for massive spatial data sets on modest computing environments<sup>†</sup> (Q4970245) (← links)
- On the choice of the mesh for the analysis of geostatistical data using R-INLA (Q5085574) (← links)
- Spatial blind source separation (Q5127210) (← links)
- Identifying radon-prone building typologies by marginal modelling (Q5129094) (← links)
- Applied Statistics (Q5242028) (← links)
- Spatial and Spatio‐temporal Bayesian Models with R‐INLA (Q5251248) (← links)
- (Q5402393) (← links)
