Clustering Part of Conditional Intensity Function of the ETAS Model

Description

A function to estimate the background seismicity rate and clustering (triggering) coefficient for a fitted ETAS model.

Usage

  rates(fit, dimyx=NULL, method="zhuang", plot.it=TRUE)

Arguments

Details

The argument dimyx determines the rectangular discretization grid dimensions. If it is given, then it must be a numeric vector of length 2 where the forst component dimyx[1] is the number of subdivisions in the y-direction (latitude) and the second component dimyx[2] is the number of subdivisions in the x-direction (longitude). The default (NULL) sets it to be dimyx=c(128, 128).

Value

If plot.it=TRUE, the function produces plots of the background seismicity rate and clustering coefficient.

If plot.it=FALSE, it returns a list of length 3, with the total spatial intensity, background seismicity rate and clustering as components (objects of im class in the package spatstat).

Author(s)

Abdollah Jalilian jalilian@razi.ac.ir

References

Zhuang, J., Ogata, Y. and Vere-Jones, D. (2005). Diagnostic analysis of space-time branching processes for earthquakes. Lecture Note in Statistics: Case Studies in Spatial Point Process Models (Baddeley, A., Gregori, P., Mateu, J., Stoica, R. and Stoyan, D.), Springer-Verlag, New York, 185, 276–292.

Zhuang, J., Ogata, Y. and Vere-Jones, D. (2002). Stochastic declustering of space-time earthquake occurrences. Journal of the American Statistical Association, 97, 369–380.

See Also

etas

Examples

  # preparing the catalog
  iran.cat <- catalog(iran.quakes, time.begin="1973/01/01",
     study.start="1996/01/01", study.end="2016/01/01",
     lat.range=c(25, 42), long.range=c(42, 63), mag.threshold=4.5)

  print(iran.cat)
  ## Not run: 
  plot(iran.cat)
## End(Not run)

  # initial parameters values
  param01 <- c(0.46, 0.23, 0.022, 2.8, 1.12, 0.012, 2.4, 0.35)

  # fitting the model and estimating the rates
  ## Not run: 
  iran.fit <- etas(iran.cat, param0=param01, no.itr=5)
  rates(iran.fit, dimyx=c(200, 250))
  iran.rates <- rates(iran.fit, dimyx=c(200, 250), plot.it=FALSE)
  summary(iran.rates$background)
## End(Not run)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ETAS)
Loading required package: maps

 # maps v3.1: updated 'world': all lakes moved to separate new #
 # 'lakes' database. Type '?world' or 'news(package="maps")'.  #


> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ETAS/rates.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rates
> ### Title: Clustering Part of Conditional Intensity Function of the ETAS
> ###   Model
> ### Aliases: rates
> ### Keywords: spatial math earthquake modeling
> 
> ### ** Examples
> 
> 
>   # preparing the catalog
>   iran.cat <- catalog(iran.quakes, time.begin="1973/01/01",
+      study.start="1996/01/01", study.end="2016/01/01",
+      lat.range=c(25, 42), long.range=c(42, 63), mag.threshold=4.5)
> 
>   print(iran.cat)
earthquake catalog:
  time begin 1973-01-01 
  study period: 1996-01-01  to  2016-01-01 (T = 7305 days)
geographical region:
    rectangular = [ 42 , 63 ] x [ 25 25 ]
threshold magnitude: 4.5
number of events:
  total events 2959 : 1240 target events,  1719 complementary events
  ( 67 events outside geographical region, 1652 events outside study period)>   ## Not run: 
> ##D   plot(iran.cat)
> ## End(Not run)
> 
>   # initial parameters values
>   param01 <- c(0.46, 0.23, 0.022, 2.8, 1.12, 0.012, 2.4, 0.35)
> 
>   # fitting the model and estimating the rates
>   ## Not run: 
> ##D   iran.fit <- etas(iran.cat, param0=param01, no.itr=5)
> ##D   rates(iran.fit, dimyx=c(200, 250))
> ##D   iran.rates <- rates(iran.fit, dimyx=c(200, 250), plot.it=FALSE)
> ##D   summary(iran.rates$background)
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>