corrections

Computes vector of correction terms for second-stage estimator
of AR parameters as described in Khismatullina, Vogt (2019).

internal

Performs a multiscale analysis of a nonparametric
regression or nonparametric regressions with time series errors. In case
of one regression, with the help of this package it is possible to detect
the regions where the trend function is increasing or decreasing.
In case of multiple regressions, the test identifies regions where
the trend functions are different from each other. See
Khismatullina and Vogt (2020) <doi:10.1111/rssb.12347>,
Khismatullina and Vogt (2022) <doi:10.48550/arXiv.2209.10841> and
Khismatullina and Vogt (2023) <doi:10.1016/j.jeconom.2021.04.010>
for more details on theory and applications.

Marina Khismatullina

MSinference

Multiscale Inference for Nonparametric Time Trend(s)

Michael Vogt

corrections function

<dl><dt>coefs</dt>
<dd>Given (estimated) coefficients of the AR time series.</dd>
<dt>var_eta</dt>
<dd>Variance of the innovation term</dd>
<dt>len</dt>
<dd>Length of the vector of the corrections</dd></dl>

Arguments

Computes vector of correction terms for second-stage estimator
of AR parameters as described in Khismatullina, Vogt (2019). — corrections

<dl>

<dt>coefs</dt>
<dd>Given (estimated) coefficients of the AR time series.</dd>


<dt>var_eta</dt>
<dd>Variance of the innovation term</dd>


<dt>len</dt>
<dd>Length of the vector of the corrections</dd>

</dl>

corrections: Computes vector of correction terms for second-stage estimator of AR parameters as described in Khismatullina, Vogt (2019).

Description

Usage

Value

Arguments