lfit {sasLM} | R Documentation |
Linear Fit
Description
Fits a least square linear model.
Usage
lfit(x, y, eps=1e-8)
Arguments
x |
a result of ModelMatrix |
y |
a column vector of response, dependent variable |
eps |
Less than this value is considered as zero. |
Details
Minimum version of least square fit of a linear model
Value
coeffcients |
beta coefficients |
g2 |
g2 inverse |
rank |
rank of the model matrix |
DFr |
degree of freedom for the residual |
SSE |
sum of squares error |
SST |
sum of squares total |
DFr2 |
degree of freedom of the residual for beta coefficient |
Author(s)
Kyun-Seop Bae k@acr.kr
See Also
Examples
f1 = uptake ~ Type*Treatment + conc
x = ModelMatrix(f1, CO2)
y = model.frame(f1, CO2)[,1]
lfit(x, y)
[Package sasLM version 0.10.4 Index]