Description Usage Arguments Details Value Author(s) References Examples
This metric considers inter event interval for point processes.
1 2 |
S1 |
marked point process data. |
S2 |
marked point process data. |
measure |
|
M |
a precision matrix for filter of marks, i.e., exp( - r' M r) is used for filtering marks. It should be symmetric and positive semi-definite. |
window.length |
width of the window used for splitting the original MPP. |
variant |
choose from two variants "spike-weighted" or "time-weighted". |
abs.tol |
absolute tolerance for numerical integration. |
iei
computes inter event interval-based measure between MPP realizations. iei for simple point process does not have any tuning parameter, which can be a desirable property for data analysis. However, it's computational cost is relatively higher than other metrics.
Similarity or distance between two inputs (marked) point process S1 and S2.
Hideitsu Hino hinohide@cs.tsukuba.ac.jp, Ken Takano, Yuki Yoshikawa, and Noboru Murata
T. Kreuz, J.S. Haas, A. Morelli, H.D.I. Abarbanel, and A. Politi. Measuring spike train synchrony, Journal of Neuroscience Methods, Vol. 165(1), pp. 151-161, 2007.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ##The aftershock data of 26th July 2003 earthquake of M6.2 at the northern Miyagi-Ken Japan.
data(Miyagi20030626)
## time longitude latitude depth magnitude
## split events by 7-hour
sMiyagi <- splitMPP(Miyagi20030626,h=60*60*7,scaleMarks=TRUE)$S
N <- 5
sMat <- matrix(0,N,N)
cat("calculating intensity inner product...")
for(i in 1:(N)){
cat(i," ")
for(j in i:N){
S1 <- sMiyagi[[i]]$time;S2 <- sMiyagi[[j]]$time
sMat[i,j] <- ieimetric(S1,S2,M=diag(1,4))
}
}
sMat <- sMat+t(sMat)
tmpd <- diag(sMat) <- diag(sMat)/2
sMat <- sMat/sqrt(outer(tmpd,tmpd))
image(sMat)
|
calculating intensity inner product...1 2 3 4 5
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