Dear all,
Can I ask something about programming in marginal distribution for spatial
extreme?
I really stuck on my coding to obtain the parameter estimation for
univariate or marginal distribution for new model in spatial extreme.
I want to run my data in order to get the parameter estimation value for 25
stations in one table. But I really didn't get the idea of the correct
coding. Here I attached my coding
x <- data.matrix(Ozone_weekly2)
x
head(gev.fit)[1:4]
ti = matrix(ncol = 3, nrow = 888)
ti[,1] = seq(1, 888, 1)
ti[,2]=sin(2*pi*(ti[,1])/52)
ti[,3]=cos(2*pi*(ti[,1])/52)
for(i in 1:nrow(x))
+ { for(j in 1:ncol(x))
+ {x[i,j] = 1}}
My problem is highlighted in red color.
And if are not hesitate to all. Can someone share with me the procedure,
how can I map my data using spatial extreme.
For example:
After I finish my marginal distribution, what the next procedure. It is I
need to get the spatial independent value.
That's all
Thank you.
--
"..Millions of trees are used to make papers, only to be thrown away
after a couple of minutes reading from them. Our planet is at stake. Please
be considerate. THINK TWICE BEFORE PRINTING THIS.."
DISCLAIMER: This email \ and any files transmitte...{{dropped:24}}
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
