Package: aTSA 3.1.2.1
Debin Qiu
aTSA: Alternative Time Series Analysis
Contains some tools for testing, analyzing time series data and fitting popular time series models such as ARIMA, Moving Average and Holt Winters, etc. Most functions also provide nice and clear outputs like SAS does, such as identify, estimate and forecast, which are the same statements in PROC ARIMA in SAS.
Authors:
aTSA_3.1.2.1.tar.gz
aTSA_3.1.2.1.tar.gz(r-4.5-noble)aTSA_3.1.2.1.tar.gz(r-4.4-noble)
aTSA_3.1.2.1.tgz(r-4.4-emscripten)aTSA_3.1.2.1.tgz(r-4.3-emscripten)
aTSA.pdf |aTSA.html✨
aTSA/json (API)
# Install 'aTSA' in R: |
install.packages('aTSA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:199cb8e120. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
Exports:accurateadf.testarch.testcoint.testecmestimateexpsmoothforecastHoltidentifykpss.testMApp.teststationary.teststepartrend.testts.diagWinters
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Accurate Computation | accurate |
Augmented Dickey-Fuller Test | adf.test |
ARCH Engle's Test for Residual Heteroscedasticity | arch.test |
Alternative Time Series Analysis | aTSA |
Cointegration Test | coint.test |
Error Correction Model | ecm |
Estimate an ARIMA Model | estimate |
Simple Exponential Smoothing | expsmooth |
Forecast From ARIMA Fits | forecast |
Holt's Two-parameter Exponential Smoothing | Holt |
Identify a Time Series Model | identify |
Kwiatkowski-Phillips-Schmidt-Shin Test | kpss.test |
Moving Average Filter | MA |
Phillips-Perron Test | pp.test |
Stationary Test for Univariate Time Series | stationary.test |
Stepwise Autoregressive Model | stepar |
Trend Test | trend.test |
Diagnostics for ARIMA fits | ts.diag |
Winters Three-parameter Smoothing | Winters |