Pages that link to "Item:Q3100796"
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The following pages link to Bayesian Semiparametric Intensity Estimation for Inhomogeneous Spatial Point Processes (Q3100796):
Displaying 15 items.
- Variational approach for spatial point process intensity estimation (Q395994) (← links)
- Meta-analysis of functional neuroimaging data using Bayesian nonparametric binary regression (Q439162) (← links)
- Space-time inhomogeneous background intensity estimators for semi-parametric space-time self-exciting point process models (Q778876) (← links)
- Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis (Q997304) (← links)
- Convex and non-convex regularization methods for spatial point processes intensity estimation (Q1746561) (← links)
- Consistent parametric estimation of the intensity of a spatial-temporal point process (Q1765758) (← links)
- A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA) (Q1939998) (← links)
- Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates (Q2291306) (← links)
- A weighted estimating equation approach for inhomogeneous spatial point processes (Q3067013) (← links)
- Bayesian P-splines and advanced computing in R for a changepoint analysis on spatio-temporal point processes (Q5222497) (← links)
- Variable selection for inhomogeneous spatial point process models (Q5256382) (← links)
- Bayesian Wombling for Spatial Point Processes (Q5850974) (← links)
- Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation (Q5872952) (← links)
- Semiparametric Multinomial Logistic Regression for Multivariate Point Pattern Data (Q5881152) (← links)
- Heterogeneity pursuit for spatial point pattern with application to tree locations: a Bayesian semiparametric recourse (Q6626411) (← links)
