View source: R/plot.maxPersistence.R
plot.maxPersistence | R Documentation |
The function plot.maxPersistence
plots an object of class maxPersistence
, for the selection of the optimal smoothing parameter for persistent homology.
For each value of the smoothing parameter, the plot shows the number of detected features, their persistence, and a bootstrap confidence band.
## S3 method for class 'maxPersistence'
plot(
x, features = "dimension", colorBand = "pink",
colorBorder = NA, ...)
x |
an object of class |
features |
string: if "all" then all the features are plotted; if "dimension" then only the features of the dimension used to compute the confidence band are plotted. |
colorBand |
the color for filling the confidence band. The default is "pink". (NA leaves the band unfilled) |
colorBorder |
the color to draw the border of the confidence band. The default is NA and omits the border. |
... |
additional graphical parameters. |
Fabrizio Lecci
Chazal F, Cisewski J, Fasy BT, Lecci F, Michel B, Rinaldo A, Wasserman L (2014). "Robust Topological Inference: distance-to-a-measure and kernel distance."
Fasy BT, Lecci F, Rinaldo A, Wasserman L, Balakrishnan S, Singh A (2013). "Statistical Inference For Persistent Homology." (arXiv:1303.7117). Annals of Statistics.
maxPersistence
## input data: circle with clutter noise
n <- 600
percNoise <- 0.1
XX1 <- circleUnif(n)
noise <- cbind(runif(percNoise * n, -2, 2), runif(percNoise * n, -2, 2))
X <- rbind(XX1, noise)
## limits of the Gird at which the density estimator is evaluated
Xlim <- c(-2, 2)
Ylim <- c(-2, 2)
lim <- cbind(Xlim, Ylim)
by <- 0.2
B <- 80
alpha <- 0.05
## candidates
parametersKDE <- seq(0.1, 0.5, by = 0.2)
maxKDE <- maxPersistence(kde, parametersKDE, X, lim = lim, by = by,
bandFUN = "bootstrapBand", B = B, alpha = alpha,
parallel = FALSE, printProgress = TRUE)
print(summary(maxKDE))
par(mfrow = c(1, 2))
plot(X, pch = 16, cex = 0.5, main = "Circle")
plot(maxKDE)
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