lm.fit.recursive: Recursive Least Squares
In quantreg: Quantile Regression
lm.fit.recursive R Documentation
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 documentation built on Oct. 22, 2024, 5:07 p.m.
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| lm.fit.recursive | R Documentation |
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
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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