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etasFLP (version 1.2.1)

Mixed FLP and ML Estimation of ETAS Space-Time Point Processes

Description

Estimation of the components of an ETAS model for earthquake description. Non-parametric background seismicity can be estimated through FLP (Forward Likelihood Predictive), while parametric components are estimated through maximum likelihood. The two estimation steps are alternated until convergence is obtained. For each event the probability of being a background event is estimated and used as a weight for declustering steps. Many options to control the estimation process are present, together with some diagnostic tools. Some descriptive functions for earthquakes catalogs are present; also plot, print, summary, profile methods are defined for main output (objects of class 'etasclass').

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Version

Install

install.packages('etasFLP')

Monthly Downloads

198

Version

1.2.1

License

GPL (>= 2)

Maintainer

Marcello Chiodi

Last Published

April 16th, 2015

Functions in etasFLP (1.2.1)

italycatalog

Small sample catalog of italian earthquakes
xy.grid

Creates a 2-d grid
simpson.coeff

Computes Simpson integration rule coefficients
magn.plot

Transformed plot of the magnitudes distribution of an earthquakes catalog
b.guten

Estimates the parameter of the Gutenberg-Richter law.
MLA.freq

Display a pretty frequency table
compare.etasclass

Compare two etasclass objects
time2date

Date time conversion tools
etasclass

Mixed estimation of an ETAS model
etasFLP-package

Mixed FLP and ML Estimation of ETAS Space-Time Point Processes
print.etasclass

Print method for etasclass objects
eqcat

Check earthquake catalog
californiacatalog

Sample catalog of North California earthquakes
etas.starting

Guess starting values of ETAS parameters (beta-version). Only from package version 1.2.0
profile.etasclass

profile method for etasclass objects (ETAS model)
summary.etasclass

Summary method for etasclass objects
plot.etasclass

Plot method for etasclass objects
etasFLP-internal

Internal etasFLP functions
plot.profile.etasclass

plot method for profile.etasclass objects (profile likelihood of ETAS model)
kde2dnew.fortran

A 2-d normal kernel estimator
bwd.nrd

Silverman's rule optimal for the estimation of a kernel bandwidth