Package index • ETAS.inlabru

All functions

IntInjectionIntensity() Inv_IntInjectionIntensity(): Injection Rate function calculations

Int_ETAS_time_trig_function(): Integrated Omori's law

Inv_Int_ETAS_time_trig_function(): Inverse of integrated Omori's law

It_df(): Function to calculate the integral of Omori's law

Temporal.ETAS(): Function to fit Hawkes process model

Temporal.ETAS.fit(): Fits the remporal ETAS model and returns the results. This function decomposes the input.list for the `Hawkes.bru2“ function.

Temporal.ETAS.forecast(): Title

breaks_exp(): Find breaks point for 1D grid

compute_grid(): Function to compute the integral of Omori's law efficiently

cond_lambda(): ETAS conditional intensity - used by inlabru

create_input_list_temporal_noCatalogue(): Function to create a default input list for the ETAS Hawkes temporal model where no catalogue is specified in the input file

create_input_list_temporal_withCatalogue(): Function to create a default input file for the ETAS Hawkes temporal model where a catalogue is specified in the input file.

exp_t(): Copula transformation from a standard Normal distribution to an Exponential distribution

gamma_t(): Copula transformation from a standard Normal distribution to a Gamma distribution

generate_temporal_ETAS_synthetic(): Generates a synthetic catalogue using the ETAS model

get_posterior_N(): Plot the posterior distribution of the expected number of events

get_posterior_param(): Retrieve posterior distribution of ETAS parameters

gt(): ETAS triggering function - used by inlabru

horus: HORUS Ita Catalogue

inv_exp_t(): Copula transformation from an Exponential to a standard Normal distribution

inv_gamma_t(): Copula transformation from an Gamma to a standard Normal distribution

inv_loggaus_t(): Copula transformation from an Log-Normal to a standard Normal distribution

inv_unif_t(): Copula transformation from an Uniform to a standard Normal distribution

lambda_N(): Calculate the integral of the ETAS conditional intensity

log_Lambda_h(): Logarithm of the integral of the ETAS triggering function

loggaus_t(): Copula transformation from a standard Normal distribution to a Log-Normal distribution

omori(): Function to calculate Omori's law

omori_plot_posterior(): Function to plot Omori's law corresponding to different posterior samples

omori_plot_prior(): Function to plot Omori's law corresponding to different prior samples

post_pairs_plot(): Plot the posterior densities of the ETAS parameters

post_sampling(): Sample from the posterior of the ETAS parameters

sample_GR_magnitudes(): Return a sample of magnitudes drawn from the GR distribution

sample_temporal_ETAS_daughters(): Generate a sample of new events data.frame(t_i, M_i) of length n.ev for one parent event occuring at time t_h using the ETAS model.

sample_temporal_ETAS_generation(): Take all previous parent events from Ht=data.frame[ts, magnitudes] and generates their daughters events using the ETAS model

sample_temporal_ETAS_times(): Sampling times for events triggered by a parent at th according to the ETAS triggering function

sample_temporal_injection_events(): Title

time_grid(): Generate a set of time bins for a specific event.

triggering_fun_plot(): Function to plot the ETAS triggering function corresponding to different posterior samples

triggering_fun_plot_prior(): Function to plot the ETAS triggering function corresponding to different prior samples

unif_t(): Copula transformation from a standard Normal distribution to a Uniform distribution