Description Usage Arguments Value Examples
This function allows you to estimate mixed causal-noncausal MARX models by t-MLE (compatible with most functions in lm() class).
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y |
Data vector of time series observations. |
x |
Matrix of data (every column represents one time series). Specify NULL or "not" if not wanted. |
p_C |
Number of lags to be included. |
p_NC |
Number of leads to be included. |
... |
Other parameters. |
object |
An object of the class "mixed". |
An object of class "mixed"
is a list containing the following components:
coefficients |
Vector of estimated coefficients. |
se |
Standard errors of estimated coefficients. |
df.residual |
Degrees of freedom residuals. |
residuals |
Residuals. |
fitted.values |
Fitted values. |
order |
Vector containing (r,s,q), i.e. causal order r, noncausal order s, number of exogenous regressors q. |
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There were 50 or more warnings (use warnings() to see the first 50)
Length Class Mode
coefficients 4 -none- numeric
se 4 -none- numeric
df.residual 1 -none- numeric
residuals 98 -none- numeric
fitted.values 98 -none- numeric
call 5 -none- call
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