Description Usage Arguments Details Value See Also Examples

Specification of a differentiable convex loss function.

1 | ```
fSolver(z, a, extra)
``` |

`z` |
Vector containing observed response |

`a` |
Matrix with active constraints |

`extra` |
List with element |

This function is called internally in `activeSet`

by setting `mySolver = fSolver`

. It uses
`optim()`

with `"BFGS"`

for optimization.

`x` |
Vector containing the fitted values |

`lbd` |
Vector with Lagrange multipliers |

`f` |
Value of the target function |

`gx` |
Gradient at point x |

1 2 3 4 5 6 7 | ```
##Fitting isotone regression using active set (L2-norm user-specified)
set.seed(12345)
y <- rnorm(9) ##response values
w <- rep(1,9) ##unit weights
btota <- cbind(1:8, 2:9) ##Matrix defining isotonicity (total order)
fit.convex <- activeSet(btota, fSolver, fobj = function(x) sum(w*(x-y)^2),
gobj = function(x) 2*drop(w*(x-y)), y = y, weights = w)
``` |

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