.. _method-efficient_global-initial_samples:

"""""""""""""""
initial_samples
"""""""""""""""


Initial number of samples for sampling-based methods


.. toctree::
   :hidden:
   :maxdepth: 1



**Specification**

- *Alias:* None

- *Arguments:* INTEGER

- *Default:* (d+1)(d+2)/2


**Description**


The ``initial_samples`` keyword is used to define the number of initial
samples (i.e., randomly chosen sets of variable values) at which to
execute a model.  The initial samples may later be augmented in an
iterative process.

*Default Behavior*

By default, Dakota will use the minimum number of samples required by
the chosen method.

*Usage Tips*

To obtain linear sensitivities or to construct a linear response
surface, at least dim+1 samples should be used, where "dim" is the
number of variables.  For sensitivities to quadratic terms or
quadratic response surfaces, at least (dim+1)(dim+2)/2 samples are
needed.  For uncertainty quantification, we recommend at least 10*dim
samples.  For ``variance_based_decomp``, we recommend hundreds to
thousands of samples.  Note that for ``variance_based_decomp``, the
number of simulations performed will be N*(dim+2).



**Examples**



.. code-block::

    method
      sampling
        sample_type random
        initial_samples = 20
        refinement_samples = 5




