TSestModel {dse1} | R Documentation

## Estimated Time Series Model

### Description

Object containing a time series model, data, and estimation information.

### Usage

        TSestModel(obj)
        ## S3 method for class 'TSestModel':
        TSestModel(obj)
        is.TSestModel(obj)

### Arguments

`obj` | in the first usage an object from which a TSestModel object can be extracted (or constructed).

### Details

The TSestModel class of objects are generated by estimation methods. See, for example, `estVARXls`. They contains a time series model (TSmodel), data (TSdata), and information obtained by evaluating the model with the data in an element called `estimates` containing:

like
  The negative log likelihood function value (a vector of the total, constant, the det part, and the cov part)
cov
  The estimated residual covariance.
pred
  The one step ahead predictions (see predictT below). These are aligned with output data so that residuals are pred[1:sampleT,] - output[1:sampleT,]
sampleT
  The end of the period (starting from 1) for which output is used for calculating one step ahead predictions.
predictT
  The end of the period for which the model is simulated. sampleT must be less than or equal predictT. If predictT is greater than sampleT then each step ahead beyond sampleT is based on the prediction of the previous step and not corrected by the prediction error.

The element `estimates` may optionally also contain and element `filter` which may have

state
  The one step ahead (filter) estimate of the state E[z(t)|y(t-1), u(t)]. Note: In the case where there is no input u this corresponds to what would usually be called the predicted state - not the filtered state.
track
  The estimated state tracking error P(t|t-1). Again note, this corresponds to the predicted tracking eror not the filtered tracking error. This is NULL for innovations models.
smooth
  a list of:
state
  The smoother (two sided filter) estimate of the state E[z(t)| sampleT].
track
  The smoothed estimate of the state tracking error P(t|sampleT). This is NULL for innovations models.

### See Also

`estVARXls`, `TSmodel`, `TSdata`

[Package Contents]