sasLM (version 0.6.0)

lfit: 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.

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

R2

R-squared

n

count of observations

R2ADJ

Adjusted R-squared

Details

Minimum version of least square fit of a linear model

See Also

ModelMatrix

Examples

# NOT RUN {
f1 = uptake ~ Type*Treatment + conc
x = ModelMatrix(f1, CO2)
y = model.frame(f1, CO2)[,1]
lfit(x, y)
# }