ComputeBest_t

Runs Monte Carlo simulation for different values of \(\alpha\) and
 \(\beta\) and computes a specified number of t-points that minimises
 the determinant of the asymptotic covariance matrix.

Simulation

Estimate the four parameters of stable laws using maximum
likelihood method, generalised method of moments with
finite and continuum number of points, iterative
Koutrouvelis regression and Kogon-McCulloch method.  The
asymptotic properties of the estimators (covariance
matrix, confidence intervals) are also provided.

Georgi Boshnakov

StableEstim

Estimate the Four Parameters of Stable Laws using Different
Methods

Tarak Kharrat

ComputeBest_t function

<dl> <dt>AlphaBetaMatrix</dt>
<dd>values of the parameter \(\alpha\) and \(\beta\) from which we
 simulate the data. By default, the values of \(\gamma\) and
 \(\delta\) are set to 1 and 0, respectively;
 a \(2 \times n\) matrix.</dd> <dt>nb_ts</dt>
<dd>vector of numbers of t-points to use for the minimisation;
 default = <code>seq(10, 100, 10)</code>.</dd> <dt>alphaReg</dt>
<dd>value of the regularisation parameter; numeric, default = 0.001.</dd> <dt>FastOptim</dt>
<dd>Logical flag; if set to TRUE, <code>optim</code> with "Nelder-Mead" method
 is used (fast but not accurate). Otherwise, <code>nlminb</code> is used
 (more accurate but slower).</dd> <dt>...</dt>
<dd>Other arguments to pass to the optimisation function.</dd></dl>

Arguments

Monte Carlo simulation to investigate the optimal number of
  points to use in the moment conditions — ComputeBest_t

<dl>

 <dt>AlphaBetaMatrix</dt>
<dd>values of the parameter \(\alpha\) and \(\beta\) from which we
 simulate the data. By default, the values of \(\gamma\) and
 \(\delta\) are set to 1 and 0, respectively;
 a \(2 \times n\) matrix.</dd>

 <dt>nb_ts</dt>
<dd>vector of numbers of t-points to use for the minimisation;
 default = <code>seq(10, 100, 10)</code>.</dd>

 <dt>alphaReg</dt>
<dd>value of the regularisation parameter; numeric, default = 0.001.</dd>

 <dt>FastOptim</dt>
<dd>Logical flag; if set to TRUE, <code>optim</code> with "Nelder-Mead" method
 is used (fast but not accurate). Otherwise, <code>nlminb</code> is used
 (more accurate but slower).</dd>

 <dt>...</dt>
<dd>Other arguments to pass to the optimisation function.</dd>

</dl>

ComputeBest_t: Monte Carlo simulation to investigate the optimal number of points to use in the moment conditions

Description

Usage

Value

Arguments

See Also