Functions for Time Series Analysis
Deprecated functions in package funtimes.
funtimes: Functions for Time Series Analysis
Change Point Detection in Autoregressive Time Series
Estimation of Autoregressive (AR) Parameters
Testing for Change Points in Time Series via Polynomial Regression
Beale's Estimator and Sample Size
BIC-Based Spatio-Temporal Clustering
Out-of-sample Tests of Granger Causality
Out-of-sample Tests of Granger Causality using (Restricted) Vector Aut...
Cross-Correlation of Autocorrelated Time Series
Slide-Level Time Series Clustering
Change Point Detection in Time Series via a Linear Regression with Tem...
Window-Level Time Series Clustering
Downhill Riding (DR) Procedure
Defunct functions in package funtimes.
HVK Estimator
Interval-Based Tails Comparison
Change Point Test for Regression
Change Point Test for Regression
Sieve Bootstrap Based Test for the Null Hypothesis of no Trend
Sieve Bootstrap Based Test for the Null Hypothesis of no Trend
Clustering Purity
Quantile-Based Tails Comparison
Time Series Clustering based on Trend Synchronism
Time Series Trend Synchronism Test
Time Series Clustering based on Trend Synchronism
Time Series Trend Synchronicity Test
Interval-Based Tails Comparison
Quantile-Based Tails Comparison
WAVK Statistic
WAVK Trend Test
WAVK Trend Test
Nonparametric estimators and tests for time series analysis. The functions use bootstrap techniques and robust nonparametric difference-based estimators to test for the presence of possibly non-monotonic trends and for synchronicity of trends in multiple time series.