gaussian_kernel

Calculate a discretization of the 2D Gaussian Kernel

General optimisation and specific tools for the parameter estimation (i.e. calibration) of complex models, including stochastic ones. It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as base::optim.
It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients.
Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided.
See <https://roliveros-ramos.github.io/calibrar/> for more details.

Ricardo OliverosRamos

calibrar

Automated Parameter Estimation for Complex Models

Ricardo Oliveros-Ramos

gaussian_kernel function

<dl><dt>par</dt>
<dd>A list, including the mean and covariance matrix.</dd>
<dt>lower</dt>
<dd>A vector, indicating the lower bound for the calculation.</dd>
<dt>upper</dt>
<dd>A vector, indicating the upper bound for the calculation.</dd>
<dt>n</dt>
<dd>The number of cells for each dimension, can be one or two numbers.</dd>
<dt>checkSymmetry</dt>
<dd>TRUE by default, checks if the covariance matrix is symmetric.</dd>
<dt>...</dt>
<dd>Additional arguments, currently not used.</dd></dl>

Arguments

Calculate a discretization of the 2D Gaussian Kernel — gaussian_kernel

<dl>

<dt>par</dt>
<dd>A list, including the mean and covariance matrix.</dd>


<dt>lower</dt>
<dd>A vector, indicating the lower bound for the calculation.</dd>


<dt>upper</dt>
<dd>A vector, indicating the upper bound for the calculation.</dd>


<dt>n</dt>
<dd>The number of cells for each dimension, can be one or two numbers.</dd>


<dt>checkSymmetry</dt>
<dd>TRUE by default, checks if the covariance matrix is symmetric.</dd>


<dt>...</dt>
<dd>Additional arguments, currently not used.</dd>

</dl>

gaussian_kernel: Calculate a discretization of the 2D Gaussian Kernel

Description

Usage

Value

Arguments