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iwl
2009 Jul 01
1
Iteratively Reweighted Least Squares of nonlinear regression
Dear all,
When doing nonlinear regression, we normally use nls if e are iid normal.
i learned that if the form of the variance of e is not completely known,
we can use the IRWLS (Iteratively Reweighted Least Squares )
algorithm:
for example, var e*i =*g0+g1*x*1
1. Start with *w**i = *1
2. Use least squares to estimate b.
3. Use the residuals to estimate g, perhaps by regressing e^2 on *x*.
4. Recompute the weights and goto 2.
Continue until convergence
i was wonde...
2009 Mar 12
1
zooreg and lmrob problem (bug?)
...ficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 630.2021 38.5583 16.344 <2e-16 ***
seq(58) -0.9366 1.1639 -0.805 0.424
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Robust residual standard error: 147.3
Convergence in 8 IRWLS iterations
Robustness weights:
4 weights are ~= 1. The remaining 54 ones are summarized as
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.5522 0.8858 0.9537 0.9212 0.9831 0.9990
Algorithmic parameters:
tuning.chi bb tuning.psi refine.tol rel.tol
1.5476400 0.5000000 4....