sim_FARMA

Simulating data from a stationary functional autoregressive moving average process

time series

Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.

Han Lin Shang

ftsa

Functional Time Series Analysis

Rob Hyndman

sim_FARMA function

<dl> <dt>n</dt>
<dd>Number of curves</dd> <dt>d</dt>
<dd>Memory parameter</dd> <dt>no_grid</dt>
<dd>Number of grid points within a unit interval</dd> <dt>seed_number</dt>
<dd>Psuedo-random seed number</dd> <dt>process</dt>
<dd>FAR or FARMA process</dd></dl>

Arguments

Author

Simulating data from a functional autoregressive moving average process — sim_FARMA

<dl>

 <dt>n</dt>
<dd>Number of curves</dd>

 <dt>d</dt>
<dd>Memory parameter</dd>

 <dt>no_grid</dt>
<dd>Number of grid points within a unit interval</dd>

 <dt>seed_number</dt>
<dd>Psuedo-random seed number</dd>

 <dt>process</dt>
<dd>FAR or FARMA process</dd>

</dl>

sim_FARMA: Simulating data from a functional autoregressive moving average process

Description

Usage

Value

Arguments

Author

References

See Also

Examples