Pages that link to "Item:Q2874951"
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The following pages link to Logistic regression for spatial Gibbs point processes (Q2874951):
Displaying 18 items.
- Variational estimators for the parameters of Gibbs point process models (Q358135) (← links)
- Penalized composite likelihoods for inhomogeneous Gibbs point process models (Q1662861) (← links)
- Convex and non-convex regularization methods for spatial point processes intensity estimation (Q1746561) (← links)
- Spatial logistic regression and change-of-support in Poisson point processes (Q1952095) (← links)
- Spatiotemporal wildfire modeling through point processes with moderate and extreme marks (Q2686054) (← links)
- Adjusted composite likelihood ratio test for spatial Gibbs point processes (Q5222385) (← links)
- Stochastic Quasi-Likelihood for Case-Control Point Pattern Data (Q5231492) (← links)
- Semiparametric Multinomial Logistic Regression for Multivariate Point Pattern Data (Q5881152) (← links)
- The Poisson transform for unnormalised statistical models (Q5963779) (← links)
- What is the effective sample size of a spatial point process? (Q6051621) (← links)
- Should We Condition on the Number of Points When Modelling Spatial Point Patterns? (Q6067599) (← links)
- Inference for low‐ and high‐dimensional inhomogeneous Gibbs point processes (Q6073438) (← links)
- Pairwise interaction function estimation of stationary Gibbs point processes using basis expansion (Q6136585) (← links)
- Data-driven chimney fire risk prediction using machine learning and point process tools (Q6138624) (← links)
- Point pattern analysis on a region of a sphere (Q6539175) (← links)
- Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity (Q6552787) (← links)
- kppmenet: combining the kppm and elastic net regularization for inhomogeneous Cox point process with correlated covariates (Q6571988) (← links)
- On the Conway-Maxwell-Poisson point process (Q6579738) (← links)
