pcacf_pwn_var

Computes the variances of sample periodic autocorrelations from
 periodic white noise.

pcstat

Classes and methods for modelling and simulation of
periodically correlated (PC) and periodically integrated time
series. Compute theoretical periodic autocovariances and related
properties of PC autoregressive moving average models. Some original
methods including Boshnakov & Iqelan (2009)
<doi:10.1111/j.1467-9892.2009.00617.x>, Boshnakov (1996)
<doi:10.1111/j.1467-9892.1996.tb00281.x>.

Georgi Boshnakov

pcts

Periodically Correlated and Periodically Integrated Time Series

pcacf_pwn_var function

<dl> <dt>lag</dt>
<dd>desired lags, a vector of positive integers.</dd> <dt>season</dt>
<dd>desired seasons.</dd> <dt>nepoch</dt>
<dd>number of epochs.</dd> <dt>period</dt>
<dd>number of seasons.</dd></dl>

Arguments

Author

Variances of sample periodic autocorrelations — pcacf_pwn_var

<dl>

 <dt>lag</dt>
<dd>desired lags, a vector of positive integers.</dd>

 <dt>season</dt>
<dd>desired seasons.</dd>

 <dt>nepoch</dt>
<dd>number of epochs.</dd>

 <dt>period</dt>
<dd>number of seasons.</dd>

</dl>

pcacf_pwn_var: Variances of sample periodic autocorrelations

Description

Usage

Value

Arguments

Author

Details

References

Examples