Description Usage Arguments Value Author(s) Examples
View source: R/regimes.plot.MSAR.R
Plot MSAR time series with regimes materialized by gray boxes.
1 2 |
res |
list obtained from fit.MSAR fonction as result of MSAR fitting |
data |
data to plot |
ex |
number of sample |
nc |
component number (useful for multivariate time series) |
col.l |
color of time series (default is red) |
ylim |
range for the plotted 'y' values, defaulting to the range of the finite values of 'y' |
xlab |
a title for the x axis |
ylab |
a title for the y axis |
d |
dimension to be plot (for multivariate cases). Default is 1. |
dt |
time step (default=1) |
lwd |
width of the line |
cex |
symbols/text size |
Returns a plot and the regimes time series.
Valerie Monbet, valerie.monbet@univ-rennes1.fr
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | data(lynx)
T = length(lynx)
data = array(log(lynx),c(T,1,1))
theta.init = init.theta.MSAR(data,M=2,order=2,label="HH")
mod.lynx = fit.MSAR(data,theta.init)
regimes.plot.MSAR(mod.lynx,data,ylab="Captures number")
theta.init = init.theta.MSAR(data,M=2,order=2,label="NH",nh.transitions="logistic")
attributes(theta.init)
theta.init$A0 = mod.lynx$theta$A0
theta.init$A = mod.lynx$theta$A
theta.init$sigma = mod.lynx$theta$sigma
theta.init$prior = mod.lynx$theta$prior
theta.init$transmat = mod.lynx$theta$transmat
theta.init$par.trans = matrix(c(1,-1,-.2,.2),2,2)
Y = array(data[2:T,,],c(T-1,1,1))
Z = array(data[2:T,,],c(T-1,1,1))
mod.lynx = fit.MSAR(Y,theta.init,verbose=TRUE,MaxIter=20,covar.trans=Z)
regimes.plot.MSAR(mod.lynx,data,ylab="Captures number")
## Not run
# Fit Homogeneous MS-AR models - multivariate time series
#data(PibDetteDemoc)
#T = length(unique(PibDetteDemoc$year))-1
#N.samples = length(unique(PibDetteDemoc$country))
#PIB = matrix(PibDetteDemoc$PIB,N.samples,T+1)
#Dette = matrix(PibDetteDemoc$Dette,N.samples,T+1)
#Democratie = matrix(PibDetteDemoc$Democratie,N.samples,T+1)
#d = 2
#Y = array(0,c(T,N.samples,2))
#for (k in 1:N.samples) {
# Y[,k,1] = diff(log(PIB[k,]))
# Y[,k,2] = diff(log(Dette[k,]))
#}
#Democ = Democratie[,2:(T+1)]
#theta.hh.1 = init.theta.MSAR(Y,M=4,order=1,label="HH")
#res.hh = fit.MSAR(Y,theta.hh.1,verbose=TRUE,MaxIter=200)
#par(mfrow=c(2,1))
#regimes.plot.MSAR(res.hh,Y,ex=30,ylab="GDP")
#regimes.plot.MSAR(res.hh,Y,ex=30,nc=2,ylab="Debt")
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