Pages that link to "Item:Q3077777"

The following pages link to Structured Spatio-Temporal Shot-Noise Cox Point Process Models, with a View to Modelling Forest Fires (Q3077777):

Displaying 26 items.

• Estimating second-order characteristics of inhomogeneous spatio-temporal point processes (Q479151) (← links)
• On the use of particle Markov chain Monte Carlo in parameter estimation of space-time interacting discs (Q479154) (← links)
• Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes (Q830443) (← links)
• Spatio-temporal model for a random set given by a union of interacting discs (Q1930621) (← links)
• Multifractal point processes and the spatial distribution of wildfires in French Mediterranean regions (Q2066243) (← links)
• Forecasting counting and time statistics of compound Cox processes: a focus on intensity phase type process, deletions and simultaneous events (Q2066496) (← links)
• Spatial Cox processes in an infinite-dimensional framework (Q2125481) (← links)
• Modeling forest tree data using sequential spatial point processes (Q2163493) (← links)
• Generating annual fire risk maps using Bayesian hierarchical models (Q2320924) (← links)
• New Folded Models for the Log-Transformed Norwegian Fire Claim Data (Q2796943) (← links)
• Parameter estimation for inhomogeneous space-time shot-noise Cox point processes (Q2835302) (← links)
• Birth-jump processes and application to forest fire spotting (Q3304600) (← links)
• (Q3552463) (← links)
• Spatio-temporal Modelling of Weeds by Shot-noiseG Cox processes (Q4330140) (← links)
• Decomposition of Variance for Spatial Cox Processes (Q4911969) (← links)
• Spatio-temporal hierarchical Bayesian analysis of wildfires with Stochastic Partial Differential Equations. A case study from Valencian Community (Spain) (Q5037069) (← links)
• Enhancing the SPDE modeling of spatial point processes with INLA, applied to wildfires. Choosing the best mesh for each database (Q5082758) (← links)
• On Statistical Inference for the Random Set Generated Cox Process with Set‐marking (Q5122912) (← links)
• Quantification of annual wildfire risk; A spatio-temporal point process approach. (Q5148616) (← links)
• Fitting Nonstationary Cox Processes: An Application to Fire Insurance Data (Q5165007) (← links)
• A <i><b>J</b></i>‐function for Inhomogeneous Spatio‐temporal Point Processes (Q5251495) (← links)
• A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes (Q6100557) (← links)
• Data-driven chimney fire risk prediction using machine learning and point process tools (Q6138624) (← links)
• Assessing minimum contrast parameter estimation for spatial and spatiotemporal log-Gaussian Cox processes (Q6552765) (← links)
• A first-order, ratio-based nonparametric separability test for spatiotemporal point processes (Q6625888) (← links)
• Aspects of second-order analysis of structured inhomogeneous spatio-temporal point processes (Q6647326) (← links)