lts: Generate a Latent Time Series Object from Data

In SMAC-Group/simts: Time Series Analysis Tools

Generate a Latent Time Series Object from Data

Description

Create a lts object based on a supplied matrix or data frame. The latent time series is obtained by the sum of underlying time series.

Usage

lts(
  data,
  start = 0,
  end = NULL,
  freq = 1,
  unit_ts = NULL,
  unit_time = NULL,
  name_ts = NULL,
  name_time = NULL,
  process = NULL
)

Arguments

data	A multiple-column matrix or data.frame. It must contain at least 3 columns of which the last represents the latent time series obtained through the sum of the previous columns.
start	A numeric that provides the time of the first observation.
end	A numeric that provides the time of the last observation.
freq	A numeric that provides the rate/frequency at which the time series is sampled. The default value is 1.
unit_ts	A string that contains the unit of measure of the time series. The default value is NULL.
unit_time	A string that contains the unit of measure of the time. The default value is NULL.
name_ts	A string that provides an identifier for the time series data. Default value is NULL.
name_time	A string that provides an identifier for the time. Default value is NULL.
process	A vector that contains model names of each column in the data object where the last name is the sum of the previous names.

Value

A lts object

Author(s)

Wenchao Yang and Justin Lee

Examples

model1 = AR1(phi = .99, sigma2 = 1) 
model2 = WN(sigma2 = 1)
col1 = gen_gts(1000, model1)
col2 = gen_gts(1000, model2)
testMat = cbind(col1, col2, col1+col2)
testLts = lts(testMat, unit_time = 'sec', process = c('AR1', 'WN', 'AR1+WN'))
plot(testLts)

SMAC-Group/simts documentation built on Sept. 4, 2023, 5:25 a.m.