bfast (version 1.6.1)

bfastlite: Detect multiple breaks in a time series

Description

A combination of bfastpp and breakpoints to do light-weight detection of multiple breaks in a time series while also being able to deal with NA values by excluding them via bfastpp.

Usage

bfastlite(
  data,
  formula = response ~ trend + harmon,
  order = 3,
  breaks = "LWZ",
  lag = NULL,
  slag = NULL,
  na.action = na.omit,
  stl = c("none", "trend", "seasonal", "both"),
  decomp = c("stl", "stlplus"),
  sbins = 1,
  ...
)
bfast0n(
  data,
  formula = response ~ trend + harmon,
  order = 3,
  breaks = "LWZ",
  lag = NULL,
  slag = NULL,
  na.action = na.omit,
  stl = c("none", "trend", "seasonal", "both"),
  decomp = c("stl", "stlplus"),
  sbins = 1,
  ...
)

Value

An object of class bfastlite, with two elements:

breakpoints

output from breakpoints, containing information about the estimated breakpoints.

data_pp

preprocessed data as output by bfastpp.

Arguments

data

A time series of class ts, or another object that can be coerced to such. For seasonal components, a frequency greater than 1 is required.

formula

a symbolic description for the model in which breakpoints will be estimated.

order

numeric. Order of the harmonic term, defaulting to 3.

breaks

either a positive integer specifying the maximal number of breaks to be calculated, or a string specifying the information criterion to use to automatically determine the optimal number of breaks (see also logLik. "all" means the maximal number allowed by h is used. NULL is treated as the default of the breakpoints function (i.e. BIC).

lag

numeric. Orders of the autoregressive term, by default omitted.

slag

numeric. Orders of the seasonal autoregressive term, by default omitted.

na.action

function for handling NAs in the data (after all other preprocessing).

stl

character. Prior to all other preprocessing, STL (season-trend decomposition via LOESS smoothing) can be employed for trend-adjustment and/or season-adjustment. The "trend" or "seasonal" component or both from stl are removed from each column in data. By default ("none"), no STL adjustment is used.

decomp

"stlplus" or "stl": use the NA-tolerant decomposition package or the reference package (which can make use of time series with 2-3 observations per year)

sbins

numeric. Controls the number of seasonal dummies. If integer > 1, sets the number of seasonal dummies to use per year. If <= 1, treated as a multiplier to the number of observations per year, i.e. ndummies = nobs/year * sbins.

...

Additional arguments to breakpoints.

Author

Dainius Masiliunas, Jan Verbesselt

Examples

plot(simts) # stl object containing simulated NDVI time series
datats <- ts(rowSums(simts$time.series))
# sum of all the components (season,abrupt,remainder)
tsp(datats) <- tsp(simts$time.series) # assign correct time series attributes
plot(datats)

# Detect breaks
bp = bfastlite(datats)

# Default method of estimating breakpoints
bp[["breakpoints"]][["breakpoints"]]

# Plot
plot(bp)

# Custom method of estimating number of breaks (request 2 breaks)
strucchangeRcpp::breakpoints(bp[["breakpoints"]], breaks = 2)

# Plot including magnitude based on RMSD for the cos1 component of harmonics
plot(bp, magstat = "RMSD", magcomp = "harmoncos1", breaks = 2)