mra.plot {WASP}

Plot function: Plot original time series and decomposed frequency components

Description

Plot function: Plot original time series and decomposed frequency components

Usage

mra.plot(
  y,
  y.mra,
  limits.x,
  limits.y,
  type = c("details", "coefs"),
  ps = 12,
  ...
)

Arguments

y

Original time series (Y).

y.mra

Decomposed frequency components (d1,d2,..,aJ).

limits.x

x limit for plot.

limits.y

y limit for plot.

type

type of wavelet coefficients, details or approximations.

ps

integer; the point size of text (but not symbols).

...

arguments for plot().

Value

A plot with original time series and decomposed frequency components.

Examples

### synthetic example
# frequency, sampled from a given range
fd <- c(3, 5, 10, 15, 25, 30, 55, 70, 95)
data.SW3 <- data.gen.SW(nobs = 512, fp = c(15, 25, 30), fd = fd)

x <- data.SW3$x
xx <- padding(x, pad = "zero")
### wavelet transfrom
# wavelet family, extension mode and package
wf <- "d4" # wavelet family D8 or db4
boundary <- "periodic"
pad <- "zero"
if (wf != "haar") v <- as.integer(as.numeric(substr(wf, 2, 3)) / 2) else v <- 1

# Maximum decomposition level J
n <- length(x)
J <- ceiling(log(n / (2 * v - 1)) / log(2)) # (Kaiser, 1994)

### decomposition
x.mra <- waveslim::mra(xx, wf = wf, J = J, method = "dwt", boundary = "periodic")
x.mra.m <- matrix(unlist(x.mra), ncol = J + 1)

print(sum(abs(x - rowSums(x.mra.m[1:n, ])))) # additive check
var(x)
sum(apply(x.mra.m[1:n, ], 2, var)) # variance check

limits.x <- c(0, n)
limits.y <- c(-3, 3)
mra.plot(x, x.mra.m, limits.x, limits.y, type = "details")