NoInt2

test_nonint2.jl

using LinearRegressionKit, StatsModels, DataFrames, CSV

y = [3, 4, 4]
x = [4, 5, 6]

df = DataFrame(x= x, y= y)

f = @formula(y ~ 0 + x )
lm= regress(f, df, req_stats=["default"])
lm

delta(a,b) = if isapprox(abs(a-b), 0., atol=eps()) return 0. else return abs(a-b) end

println("NoInt2 - LRK")

println(string("delta B1 ", delta(0.727272727272727, lm.coefs[1])))
println(string("delta std err B1 ", delta(0.420827318078432E-01, lm.stderrors[1])))
println(string("delta resid std dev ", delta(0.369274472937998, lm.RMSE)))
println(string("delta R2 ", delta(0.993348115299335, lm.R2)))

# using GLM
println("NoInt2 - GLM")
lr = GLM.lm(f, df)

println(string("delta B1 ", delta(0.727272727272727, coef(lr)[1])))
println(string("delta std err B1 ", delta(0.420827318078432E-01, stderror(lr)[1])))
println(string("delta resid std dev ", delta(0.369274472937998, deviance(lr)/dof_residual(lr))))
println(string("delta R2 ", delta(0.993348115299335, r2(lr))))