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6 R session: Multivariate extremes and Bayesian inference As before, you will need to start R, and then attach the libraries ismev and evd, and the sup-
 

Summary: 6 R session: Multivariate extremes and Bayesian inference
As before, you will need to start R, and then attach the libraries ismev and evd, and the sup-
plementary R routines we have provided, using the commands:
> library(ismev)
> library(evd)
> source('Rstufflee.r')
1. In this question we carry out a simple bivariate analysis using the block­maxima ap-
proach. The dataset wind has 40 rows and 3 columns; the second and third columns
contain annual maximum wind speeds at Albany, New York and Hartford, Connecticut
(respectively) over the period 1944 to 1983.
(a) Load the data into R using:
> data(wind)
and have a look at it by typing
> wind
(b) The data we want are the annual maxima for Hartford and Albany respectively,
stored in columns 2 and 3. We extract them using
> hartford<-wind[,2]
> albany<-wind[,3]
and then recombine them into a vector of bivariate annual maxima using
> blockmax<-cbind(hartford,albany)

  

Source: Applebaum, David - Department of Probability and Statistics, University of Sheffield

 

Collections: Mathematics