data("Callcenter")
# FSSA Decomposition step:
L <- 28
U <- fssa(Callcenter, L)
plot(U, type = "values", d = 10)
plot(U, type = "vectors", d = 4)
plot(U, type = "paired", d = 6)
plot(U, type = "lcurves", d = 4, vars = 1)
plot(U, type = "lheats", d = 4)
plot(U, type = "wcor", d = 10)
plotly_funts(U$Lsingf[[1]])
plot(U$Lsingf[[2]])
if (FALSE) {
#--------------- Multivariate FSSA Example on bivariate -----------------------------
## temperature curves and smoothed images of vegetation
data("Montana")
# MFSSA Decomposition step:
L <- 45
U <- fssa(Montana, L)
plot(U, type = "values", d = 10)
plot(U, type = "vectors", d = 4)
plot(U, type = "lheats", d = 4)
plot(U, type = "lcurves", d = 4, vars = 1)
plot(U, type = "paired", d = 6)
plot(U, type = "periodogram", d = 4)
plot(U, type = "wcor", d = 10)
plotly_funts(U$Lsingf[[1]])
plot(U$Lsingf[[2]])
}
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