trend_estimate {TSsmoothing} | R Documentation |
Trend estimation with controlled smoothing.
Description
This is the main function that estimates the trend for univariate or bivariate time series for a specified smoothing level.
Usage
trend_estimate(dat, smoothing_level = NULL, lambda = NULL,
plot = TRUE, label = time(dat), jump = NULL, las = 2,
bands = TRUE)
Arguments
dat |
is a 2x2 matrix with the two time series. Each column correspond to the values at a given time. |
smoothing_level |
is a scalar between 0 and 1 that specifies the smoothing of the resulting time series tau. |
lambda |
Alternative, the function directly accepts the lambda value that corresponds to the desired smoothing level. |
plot |
is TRUE when we cant to plot of the original agaist the resulting series. |
label |
vector of characters that corresponds to the labels for each time point in the serie. |
jump |
is a vector of integers that specifies which values of labels should appear in the x labels. |
las |
is 1(2) if the x labels should be vertical (horizontal). |
bands |
is TRUE tolo include 95% confidence bands in the plots. |
Value
The smoothed series tau.
The orginal data dat.
The estimation for sigma_eta, sigma.eta
The length of the time series N.
The lambda value corresponding to the smoothing level.
The diagonal values of the estimated variance of tau, diag.var.tau
A flag that indicates if data is a bivariate time series.
Examples
# Employment in agriculture (\% of total employment) (modeled ILO estimate) in OCDE members
data(emp_agr) #It is a ts object with one single time series
sts<-trend_estimate(emp_agr,0.70)
plot_trend(sts, title="Employment in agriculture in OCDE members", xlab = "Years")
# Data Trade (\% of GDP) for USA and Mexico downloaded from
data(trade) #It is a numeric matrix with two columns
sts<-trend_estimate(trade,0.7)
plot_trend(sts, title="Trade in% of GDP",xlab="years")
ts_trade<-ts(trade, start=1969,end=2017) #We transform tade to a ts object
sts<-trend_estimate(ts_trade,0.7)
plot_trend(sts, title="Trade in% of GDP",xlab="years")