search for: optimtoyproblem

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2008 May 23
3
nls diagnostics?
...es This example is obviously stupid, but other singular gradient problems are not so obvious. If we transfer this problem to 'optim', we can get diagnostics from an eigen analysis of the hessian: dumfun <- function(x, y, one){ d <- y-(x[1]+2*x[2])*one sum(d^2) } optimToyProblem <- optim(c(a=1, b=1), dumfun, hessian=TRUE, y=DF1$y, one=DF1$one) eigen(optimToyProblem$hessian, symmetric=TRUE) $values [1] 9.000000e+01 -7.105427e-10 $vectors [,1] [,2] [1,] 0.4472136 -0.8944272 [2,] 0.8944272 0.4472136 The smallest eigenvalue...