bwd.nrd

Computes the optimal bandwidth with the Silverman's rule of thumb,
to be used for a kernel estimator with given points and weights.

Kernel

bandwidth

Estimation of the components of an ETAS (Epidemic Type Aftershock Sequence) model for earthquake description. Non-parametric background seismicity can be estimated through FLP (Forward Likelihood Predictive). New version 2.0.0: covariates have been introduced to explain the effects of external factors on the induced seismicity; the parametrization has been changed; Chiodi, Adelfio (2017)<doi:10.18637/jss.v076.i03>.

Marcello Chiodi

etasFLP

Mixed FLP and ML Estimation of ETAS Space-Time Point Processes
for Earthquake Description

Giada Adelfio

bwd.nrd function

<dl> <dt>x</dt>
<dd>numeric vector: sample points to be used for a normal kernel estimator.</dd> <dt>w</dt>
<dd>numeric vector of the same length of <code>x</code>: weights to give to the elements of <code>x</code>. Default is a vector of ones</dd> <dt>d</dt>
<dd>number of dimensions of the kernel estimator.</dd></dl>

Arguments

Author

Silverman's rule optimal for the estimation of a kernel bandwidth — bwd.nrd

<dl>

 <dt>x</dt>
<dd>numeric vector: sample points to be used for a normal kernel estimator.</dd>

 <dt>w</dt>
<dd>numeric vector of the same length of <code>x</code>: weights to give to the elements of <code>x</code>. Default is a vector of ones</dd>

 <dt>d</dt>
<dd>number of dimensions of the kernel estimator.</dd>

</dl>

bwd.nrd: Silverman's rule optimal for the estimation of a kernel bandwidth

Description

Usage

Value

Arguments

Author

Details

References

Examples