quantreg: lm.fit.recursive – R documentation

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lm.fit.recursive

Recursive Least Squares

Description

This function fits a linear model by recursive least squares. It is a utility routine for the KhmaladzeTest function of the quantile regression package.

Usage

lm.fit.recursive(X, y, int=TRUE)

Arguments

`X`	Design Matrix
`y`	Response Variable
`int`	if TRUE then append intercept to X

Value

return p by n matrix of fitted parameters, where p. The ith column gives the solution up to "time" i.

Author(s)

R. Koenker

References

A. Harvey, (1993) Time Series Models, MIT

quantreg

Quantile Regression

v5.85

GPL (>= 2)

Authors

Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Blaise Melly [ctb] (Contributions to preprocessing code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Cleve Moler [ctb] (author of several linpack routines), Yousef Saad [ctb] (author of sparskit2), Victor Chernozhukov [ctb] (contributions to extreme value inference code), Ivan Fernandez-Val [ctb] (contributions to extreme value inference code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)

Initial release