rls |

Recursive least squares regression.

The rls view of an equation displays the results of recursive least squares (rolling) regression. This view is only available for (non-panel) equations estimated by ordinary least squares without ARMA terms.

You may plot various statistics from rls by choosing an option.

Syntax

eq_name.rls(options) c(1) c(2) …

Options

r | Plot the recursive residuals about the zero line with plus and minus two standard errors. |

r,s | Plot the recursive residuals and save the residual series and their standard errors as series named R_RES and R_RESSE, respectively. |

c | Plot the recursive coefficient estimates with two standard error bands. |

c,s | Plot the listed recursive coefficients and save all coefficients and their standard errors as series named R_C1, R_C1SE, R_C2, R_C2SE, and so on. |

o | Plot the p-values of recursive one-step Chow forecast tests. |

n | Plot the p-values of recursive n-step Chow forecast tests. |

q | Plot the CUSUM (standardized cumulative recursive residual) and 5 percent critical lines. |

v | Plot the CUSUMSQ (CUSUM of squares) statistic and 5 percent critical lines. |

prompt | Force the dialog to appear from within a program. |

p | Print the view. |

Examples

equation eq1.ls m1 c tb3 gdp

eq1.rls(r,s)

eq1.rls(c) c(2) c(3)

plots and saves the recursive residual series from EQ1 and their standard errors as R_RES and R_RESSE. The third line plots the recursive slope coefficients of EQ1.

equation eq2.ls m1 c pdl(tb3,12,3) pdl(gdp,12,3)

eq2.rls(c) c(3)

eq2.rls(q)

The second command plots the recursive coefficient estimates of PDL02, the linear term in the polynomial of TB3 coefficients. The third line plots the CUSUM test statistic and the 5% critical lines.

Cross-references

See also
Equation::facbreak and
Equation::breaktest.