iStarSensitivity | R Documentation |
An helper function to provide I-Star model parameters sensitivity analysis.
iStarSensitivity(object, paramsBounds, paramSteps, ...)
object |
An object of class 'iStarEst' from the |
paramsBounds |
A matrix providing model parameters bounds to pass to |
paramSteps |
A vector of named elements representing each parameter step size to build the parameters sequences with. See 'Details' |
... |
Any other passthrough parameter |
The sensitivity analysis provided is a local one, with I-Star model paramaters being fixed one at a time. Then, for each fixed sequence of values provided for a parameter, the nonlinear problem is solved to estimate the remaing four paramaters by means of nonlinear regression.
Results of the analysis are reported along with the corresponding residul standard error (RSE) of each model being fitted. This quantity is expressed in the same dependent variable unit and best fit paramaters should be such that this quantity is minimized.
Of course, paramSteps
is related to paramsBounds
. In particular,
it should be stress that, provided step sizes will be used to built parameters
sequences from the lower bound specified in paramsBounds
until the last
multiple of the upper bound provided in paramsBounds
is reached, for each
paramater and its respective bound values. In other words, paramSteps
is not allowed to have a sequence value that goes beyond the paramsBounds
specified upper bound.
paramSteps
default is 50 for a_1
, 0.1 for a_2
and a_3
,
0.05 for a_4
and 0.01 for b_1
.
A list
with elements:
Params.Seqs
: A list
of parameters sequences evaluated
nls.impact.fits
: A list
of each model fitted with nls
Params.Sensitivity
: A matrix
contining the results of the sensitivity analysis
If paramaters fixed sequences values lead to nonlinear least squares estimation
failures, an NA
is put in place of the other paramaters being estimated
and of the residual sum of squares, as they cannot be provided.
Vito Lestingi
The Science of Algorithmic Trading and Portfolio Management (Kissell, 2013), Elsevier Science.
iStarPostTrade
,
nls
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