Multiscale Inference for Nonparametric Time Trend(s)
Computes estimator of the AR(p) coefficients by the procedure from Khi...
Computes the set of minimal intervals as described in Duembgen (2002)
Computes quantiles of the gaussian multiscale statistics.
Computes quantiles of the gaussian multiscale statistics.
Calculates the value of the test statistics both for single time serie...
Computes the location-bandwidth grid for the multiscale test.
Computes the location-bandwidth weekly grid for the multiscale test.
Computes vector of correction terms for second-stage estimator of AR p...
Computes autocovariances at lags 0 to p for the ell-th differences of ...
Computes estimator of the long-run variance of the error terms.
Multiscale Inference for Nonparametric Time Trend(s)
Carries out the multiscale test given that the values the estimatates ...
Plots SiZer map from the test results of the multiscale testing proced...
Calculates different information criterions for a single time series o...
Computes variance of AR(p) innovation terms eta.
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.