residuals_extrap

This function is the rule to extrapolate the low-frequency residuals.
If include.differenciation is <code>TRUE</code>, u(n+1)-u(n) = rho*(u(n)-u(n-1))
Else u(n+1) = rho * u(n)

internal

The twoStepsBenchmark() and threeRuleSmooth() functions allow you to
disaggregate a low-frequency time series with higher frequency time series,
using the French National Accounts methodology. The aggregated sum of the
resulting time series is strictly equal to the low-frequency time series within the
benchmarking window. Typically, the low-frequency time series is an annual one,
unknown for the last year, and the high frequency one is either quarterly or
monthly. See "Methodology of quarterly national accounts", Insee Méthodes
N°126, by Insee (2012, ISBN:978-2-11-068613-8, <https://www.insee.fr/en/information/2579410>).

Pauline Meinzel

disaggR

Two-Steps Benchmarks for Time Series Disaggregation

Arnaud Feldmann

Thomas Laurent

Franck Arnaud

Institut national de la statistique et des études économiques 

residuals_extrap function

<dl><dt>lfresiduals</dt>
<dd>the residuals to extrapolate</dd>
<dt>rho</dt>
<dd>the autocorrelation parameter of the regression</dd>
<dt>include.differenciation</dt>
<dd>a boolean, the same as submitted
to twoStepsBenchmark</dd></dl>

Arguments

Extrapolation function for the residuals in a twoStepsBenchmark — residuals_extrap

<dl>

<dt>lfresiduals</dt>
<dd>the residuals to extrapolate</dd>


<dt>rho</dt>
<dd>the autocorrelation parameter of the regression</dd>


<dt>include.differenciation</dt>
<dd>a boolean, the same as submitted
to twoStepsBenchmark</dd>

</dl>

residuals_extrap: Extrapolation function for the residuals in a twoStepsBenchmark

Description

Usage

Value

Arguments