Functions for Time Series Analysis

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Documentation for package ‘funtimes’ version 9.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

funtimes-package	funtimes: Functions for Time Series Analysis
ARest	Estimation of Autoregressive (AR) Parameters
AuePolyReg_test	Testing for Change Points in Time Series via Polynomial Regression
beales	Beale's Estimator and Sample Size
BICC	BIC-Based Spatio-Temporal Clustering
causality_pred	Out-of-sample Tests of Granger Causality
causality_predVAR	Out-of-sample Tests of Granger Causality using (Restricted) Vector Autoregression
ccf_boot	Cross-Correlation of Autocorrelated Time Series
CSlideCluster	Slide-Level Time Series Clustering
cumsumCPA_test	Change Point Detection in Time Series via a Linear Regression with Temporally Correlated Errors
CWindowCluster	Window-Level Time Series Clustering
DR	Downhill Riding (DR) Procedure
funtimes	funtimes: Functions for Time Series Analysis
GombayCPA_test	Change Point Detection in Autoregressive Time Series
HVK	HVK Estimator
mcusum_test	Change Point Test for Regression
notrend_test	Sieve Bootstrap Based Test for the Null Hypothesis of no Trend
purity	Clustering Purity
sync_cluster	Time Series Clustering based on Trend Synchronism
sync_test	Time Series Trend Synchronicity Test
tails_i	Interval-Based Tails Comparison
tails_q	Quantile-Based Tails Comparison
WAVK	WAVK Statistic
wavk_test	WAVK Trend Test