orcutt: cochrane.orcutt – R documentation

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cochrane.orcutt

Cochrane-Orcutt Estimation

Description

Interactive method using to solve first order autocorrelation problems. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals

Usage

cochrane.orcutt(reg, convergence = 8, max.iter=100)

Arguments

`reg`	a linear model built with lm function
`convergence`	decimal value to reach for convergence, 8 as default
`max.iter`	the maximum number of interactions, 100 as default

Value

An object of class "orcutt", basically a list including elements

`coefficients`	a named vector of coefficients.
`residuals`	residuals.
`fitted.values`	the fitted mean values.
`t.value`	t test of coefficients.
`p.value`	p-value of coefficients.
`call`	the matched call.
`rho`	Spearman's rho autocorrelation.
`number.interaction`	number of interaction of the model.
`DW`	vector contained Durbin-Watson statistics and p-value.

Author(s)

Stefano Spada

References

Verbeek M. (2004) A guide to modern econometrics, John Wiley & Sons Ltd, ISBN:978-88-08-17054-5

Examples

data(icecream, package="orcutt")
lm = lm(cons ~ price + income + temp, data=icecream)
coch = cochrane.orcutt(lm)
coch

orcutt

Estimate Procedure in Case of First Order Autocorrelation

v2.3

GPL-2

Authors

Stefano Spada [aut, cre], Matteo Quartagno [ctb], Marco Tamburini [ctb], David Robinson [ctb]

Initial release

2018-09-27