Regularized Point Processes and Stochastic Marginalization for Extremes


[Up] [Top]

Documentation for package ‘margEVT’ version 0.4.0

Help Pages

active_covariates Extract names of non-seasonal covariates from a fitted model
backtest Walk-forward backtesting for NHPP extreme value models
bic_nhpp Compute BIC for a fitted nhpp_fit model
bootstrap_coef Parametric bootstrap confidence intervals for model coefficients
bootstrap_rl Parametric bootstrap confidence intervals for return levels
build_cov_annual Build a covariate data frame for marginalization
build_design_matrices Build design matrices for the NHPP point process model
coef.nhpp_fit Extract coefficients of a fitted nhpp_fit model
fit_nhpp Fit a non-homogeneous point process model for extremes
fit_var_generator Fit a stationary VAR generator of covariate trajectories
is_nhpp_fit Check if an object is an nhpp_fit
logLik.nhpp_fit Log-likelihood, number of observations, and prediction for nhpp_fit
marginalize Compute unconditional return levels by marginalizing over covariates
nhpp_fit-methods Log-likelihood, number of observations, and prediction for nhpp_fit
nobs.nhpp_fit Log-likelihood, number of observations, and prediction for nhpp_fit
n_exceedances Extract the number of exceedances from a fitted model
plot.nhpp_fit Plot diagnostics for a fitted nhpp_fit object
plot.nhpp_rl Plot return-level curves from marginalize()
pp_grad Analytical gradient of the penalized negative log-likelihood
pp_nllh Penalized negative log-likelihood for the NHPP model
predict.nhpp_fit Log-likelihood, number of observations, and prediction for nhpp_fit
predict_params Compute time-varying GEV parameters from a fitted model
print.nhpp_fit Print a fitted nhpp_fit model
print.summary.nhpp_fit Print a summary of a fitted nhpp_fit model
residuals.nhpp_fit Transformed residuals of a fitted nhpp_fit model
rl_table Wide-format return level table from marginalize() output
seasonal_harmonics Seasonal Fourier harmonics
simulate_covariates Simulate stationary covariate trajectories from a VAR generator
summary.nhpp_fit Summarise a fitted nhpp_fit model