Description Usage Arguments Author(s) References Examples
Plot l1-norm of coefficients of each interval computed by DP approach
1 | DPPlotL1Norm(predictedAlpha, sol, n, p, breaks = NULL)
|
predictedAlpha |
predicted coefficients solved by DP approach |
sol |
list of change-points computed by DP approach |
n |
total number of data |
p |
dimension of data |
breaks |
list of breaks where to put a tick on the x-axis |
Bingwen Zhang
Bingwen Zhang, Jun Geng and Lifeng Lai, Detecting changes in regression models via sparse group lasso, http://users.wpi.edu/~bzhang/icassp_v1.pdf
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 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (predictedAlpha, sol, n, p, breaks = NULL)
{
predictedTheta <- matrix(0, length(sol) - 1, p)
for (i in 1:(length(sol) - 1)) {
if (i == 1) {
predictedTheta[i, ] <- predictedAlpha[i, ]
}
else {
predictedTheta[i, ] <- predictedAlpha[i, ] - predictedAlpha[i -
1, ]
}
}
t_sum = mat.or.vec(n, 1)
for (i in 1:(length(sol) - 1)) {
t_sum[sol[i]] <- sum(abs(predictedTheta[i, ]))
}
plotData <- data.frame(pos = 1:length(t_sum), normL1 = t_sum)
plotTsum <- ggplot(plotData, aes(pos, normL1))
{
if (is.null(breaks)) {
plotTsum + geom_point() + theme_bw(base_size = 16) +
xlab("Number of Observations") + ylab(expression(paste(group("|",
group("|", theta[i], "|"), "|"))[1])) + scale_x_continuous(breaks = seq(1,
n, floor(n/10)))
}
else {
plotTsum + geom_point() + theme_bw(base_size = 16) +
xlab("Number of Observations") + ylab(expression(paste(group("|",
group("|", theta[i], "|"), "|"))[1])) + scale_x_continuous(breaks = breaks)
}
}
}
|
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