aTSA v3.1.2
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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.
Functions in aTSA
Name | Description | |
adf.test | Augmented Dickey-Fuller Test | |
Winters | Winters Three-parameter Smoothing | |
Holt | Holt's Two-parameter Exponential Smoothing | |
aTSA | Alternative Time Series Analysis | |
stationary.test | Stationary Test for Univariate Time Series | |
kpss.test | Kwiatkowski-Phillips-Schmidt-Shin Test | |
stepar | Stepwise Autoregressive Model | |
ecm | Error Correction Model | |
forecast | Forecast From ARIMA Fits | |
MA | Moving Average Filter | |
estimate | Estimate an ARIMA Model | |
pp.test | Phillips-Perron Test | |
identify | Identify a Time Series Model | |
expsmooth | Simple Exponential Smoothing | |
trend.test | Trend Test | |
arch.test | ARCH Engle's Test for Residual Heteroscedasticity | |
ts.diag | Diagnostics for ARIMA fits | |
coint.test | Cointegration Test | |
accurate | Accurate Computation | |
No Results! |
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Details
Type | Package |
Date | 2015-06-19 |
License | GPL-2 | GPL-3 |
Packaged | 2015-07-08 19:18:15 UTC; Deman |
NeedsCompilation | no |
Repository | CRAN |
Date/Publication | 2015-07-08 22:37:24 |
Contributors | Debin Qiu |
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