lts: Generate Latent Time Series Object Based on Data
In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description Usage Arguments Value Author(s) Examples

Create a lts object based on a supplied matrix or data frame.

1 2	lts(data, start = 0, end = NULL, freq = 1, unit = NULL, name = NULL, process = NULL)

`data`	A multiple-column `matrix` or `data.frame`. It must contain at least 2 columns. The last column must equal to the sum of all 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 of samples. Default value is 1.
`unit`	A `string` that contains the unit expression of the frequency. Default value is `NULL`.
`name`	A `string` that provides an identifier to the data. Default value is `NULL`.
`process`	A `vector` that contains model names of decomposed and combined processes.

A lts object with the following attributes:

start: The time of the first observation
end: The time of the last observation
freq: Numeric representation of frequency
unit: String representation of the unit
name: Name of the dataset
process: A vector that contains model names of decomposed and combined processes

Wenchao

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 = 'sec', process = c('AR1', 'WN', 'AR1+WN'))
plot(testLts)