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| spatial.gev.bma-package | Fit a Hierarchical Spatial Generalized Extreme Value model that allows for Bayesian Model Averaging |
| dmvnorm | Log density of a multivariate normal distribution |
| f.double.prime | Second derivative of the posterior distribution of a spatial GEV with respect a location random effect |
| f.prime | First derivative of the posterior of a spatial GEV model with respect to a random effect in the location parameter. |
| g.double.prime | The second derivative of a GEV distribution with respect to a random effect parameter on the precision kappa |
| g.prime | The first derivative of the posterior density of a spatial GEV model with respect to a given random effect on the precision parameter. |
| gev.crps | Compute the Continuous Rank Probability Score (CRPS) |
| gev.impute | Given the output of the MCMC, return a number of samples for a new site. |
| gev.init | Initilizes a state object for a Spatial GEV distribution |
| gev.like | The log likelihood of a GEV distribution |
| gev.logscore | Compute the Log Score |
| gev.process.results | Outputs some tables from the results of Spatial GEV MCMC run |
| gev.results.init | Initialize a results object for spatial.bma.gev |
| gev.update | Updates all the parameters in a spatial GEV model |
| gev.update.hyper | Updates the Gaussian Process hyperparameters in the Spatial GEV model |
| gev.update.lambda | Update the lambda parameter in a Gaussian Process |
| gev.update.M | Sample a new model from the current model for any linear regression system |
| gev.update.tau.kappa | Update the random effects of the precision parameter in a spatial GEV model |
| gev.update.tau.mu | Internal function to update the random effects of the location parameter in a Spatial GEV model. |
| gev.update.tau.xi | Update the random effects for the shape parameter in a spatial GEV model |
| gev.update.theta | Update the linear parameters in a spatial GEV model |
| gev.z.p | Calculate the 1/p return level for a GEV distribution |
| gp.like.lambda | The likelihood of a Gaussian process used to initialize the lambda parameter |
| j.double.prime | The second derivative of a spatial GEV with respect to a random effect in the shape parameter |
| j.prime | The first derivative of the posterior density of a spatial GEV model with respect to a random effect parameter on the shape. |
| l.double.prime | The second derivative of a Gaussian process with respect to the parameter lambda. |
| l.prime | First derivative of a GP with respect to lambda |
| logdet | Returns the log determinant for a symmetric positive definite matrix. |
| make.D | Form the distance matrix for use in a Gaussian Process |
| norway | Extreme Precipitation Data at 69 Sites in Norway |
| spatial.gev.bma | Run an MCMC to fit a hierarchical spatial generalized extreme value (GEV) model with the option for Bayesian model averaging (BMA) |