Description Usage Arguments Details Examples

A fixed-point function supplied by the user is iteratively
evaluated. `addAverageDamp`

can be used to add average damping to the
function - this may have a positive effect on the speed of convergence.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
fixedPoint(fun, x0, convCrit)
addAverageDamp(fun)
addConstraintMin(fun, value)
addConstraintMax(fun, value)
convCritAbsolute(tolerance = 1e-06)
convCritRelative(tolerance = 1e-06)
addMaxIter(fun, maxIter)
addCounter(fun)
addHistory(fun)
addStorage(fun)
newtonRaphson(funList, ...)
newtonRaphsonFunction(funList)
``` |

`fun` |
the function to be evaluated in the algorithm |

`x0` |
starting value |

`convCrit` |
a function returning a logical scalar. Is called with two arguments; the first is the value from iteration n; the second is the value from iteration n-1 |

`value` |
(numeric) |

`tolerance` |
a numeric value > 0 |

`maxIter` |
maximum number of iterations |

`funList` |
(list) the functions to be evaluated in the algorithm. First element is typically the score function, second is the derivative of the score. |

`...` |
arguments passed to |

`addAverageDamp`

adds average damping to an arbitrary fixed point
function.

`addConstraintMin`

takes care that values are not below a
minimum value.

`addConstraintMax`

takes care that values are not larger than
maximum value.

`convCritAbsolute`

absolute difference as convergence criterion.

`convCritRelative`

relative (to previous iteration) absolute
difference as convergence criterion. If value is smaller than 1, absolute
difference is used.

`addMaxIter`

can be used to modify convergence criterion functions.

`addCounter`

can be used to count the number of calls of a function.

`addHistory`

can be used to save a history of results of a
function. The history is stored as a matrix, so this works best if the
return value of `fun`

is numeric.

`addStorage`

will add a storage to a function. The storage is a
list in which each result is stored. The function will coerce the return
value into a numeric.

`newtonRaphson`

finds zeroes of a function. The user can supply
the function and its first derivative. Note that the Newton Raphson
Algorithm is a special case of a fixed point algorithm thus it is
implemented using `fixedPoint`

and is only a convenience.

1 2 3 4 | ```
## Not run:
vignette("fixedPoint", "saeRobust")
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.