
"plot"(x, ..., type = c("raw", "cumsum"), plot.method = c("native", "matplot", "xyplot"), base.series = NULL, add.original = TRUE, add.residuals = TRUE)
"plot"(x, ..., type = c("raw", "cumsum"), plot.method = c("native", "matplot", "xyplot"), base.series = NULL, add.original = TRUE, add.residuals = TRUE)
"plot"(x, slice = list(), ..., type = c("raw", "cumsum"), plot.method = c("native", "matplot", "xyplot"), na.pad = c("left", "right"), base.series = NULL, add.original = TRUE, add.residuals = TRUE)
"plot"(x, ..., type = c("raw", "cumsum"), base.series = NULL, add.original = TRUE, add.residuals = TRUE, add.ranges, col = grey(c(0, 1)), zlim, at)
"plot"(x, slice, ...)
colorRamp
)z
,
a list of such vectors
or a character string.
If a list is given, corresponding list element (with recycling) will be used for each
plot panel.
For character strings, values 'free' and 'same' are allowed: 'free' means
special breakpoints' vectors (will be evaluated automatically, see description of cuts
argument in 'Details') for each component. 'same' means one breakpoints' vector for all
component (will be evaluated automatically too)
# Decompose 'co2' series with default parameters
s <- ssa(co2)
r <- reconstruct(s, groups = list(c(1, 4), c(2, 3), c(5, 6)))
# Plot full 'co2' reconstruction into trend, periodic components and noise
plot(r)
# Artificial image for 2dSSA
mx <- outer(1:50, 1:50,
function(i, j) sin(2*pi * i/17) * cos(2*pi * j/7) + exp(i/25 - j/20)) +
rnorm(50^2, sd = 0.1)
# Decompose 'mx' with default parameters
s <- ssa(mx, kind = "2d-ssa")
# Reconstruct
r <- reconstruct(s, groups = list(1, 2:5))
# Plot components, original image and residuals
plot(r)
# Plot cumulative sum of components only
plot(r, type = "cumsum", add.residuals = FALSE, add.original = FALSE)
# Real example: Mars photo
data(Mars)
# Decompose only Mars image (without backgroud)
s <- ssa(Mars, mask = Mars != 0, wmask = circle(50), kind = "2d-ssa")
# Reconstruct and plot trend
plot(reconstruct(s, 1), fill.uncovered = "original")
# Reconstruct and plot texture pattern
plot(reconstruct(s, groups = list(c(13, 14, 17, 18))))
# Decompose 'EuStockMarkets' series with default parameters
s <- ssa(EuStockMarkets, kind = "mssa")
r <- reconstruct(s, groups = list(Trend = 1:2))
# Plot original series, trend and residuals superimposed
plot(r, plot.method = "xyplot", superpose = TRUE,
auto.key = list(columns = 3),
col = c("blue", "green", "red", "violet"),
lty = c(rep(1, 4), rep(2, 4), rep(3, 4)))
# Plot the series separately
plot(r, plot.method = "xyplot", add.residuals = FALSE,
screens = list(colnames(EuStockMarkets)),
col = c("blue", "green", "red", "violet"),
lty = c(rep(1, 4), rep(2, 4), rep(3, 4)))
# 3D-SSA example (2D-MSSA)
data(Barbara)
ss <- ssa(Barbara, L = c(50, 50, 1))
plot(reconstruct(ss, groups = 1), slice = list(k = 1))
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