| intro (pdf) |
Introduction to time-series manual |
| time series (pdf) |
Introduction to time-series commands |
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| arch |
Autoregressive conditional heteroskedasticity (ARCH) family of estimators |
| arch postestimation |
Postestimation tools for arch |
| arfima |
Autoregressive fractionally integrated moving-average models |
| arfima postestimation |
Postestimation tools for arfima |
| arima (pdf) |
ARIMA, ARMAX, and other dynamic regression models |
| arima postestimation |
Postestimation tools for arima |
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| corrgram (pdf) |
Tabulate and graph autocorrelations |
| cumsp |
Cumulative spectral distribution |
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| dfactor |
Dynamic-factor models |
| dfactor postestimation |
Postestimation tools for dfactor |
| dfgls |
DF-GLS unit-root test |
| dfuller |
Augmented Dickey–Fuller unit-root test |
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| fcast compute |
Compute dynamic forecasts of dependent variables after var, svar, or vec |
| fcast graph |
Graph forecasts of variables computed by fcast compute |
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| haver |
Load data from Haver Analytics database |
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| irf |
Create and analyze IRFs, dynamic-multiplier functions, and FEVDs |
| irf add |
Add results from an IRF file to the active IRF file |
| irf cgraph |
Combine graphs of IRFs, dynamic-multiplier functions, and FEVDs |
| irf create |
Obtain IRFs, dynamic-multiplier functions, and FEVDs |
| irf ctable |
Combine tables of IRFs, dynamic-multiplier functions, and FEVDs |
| irf describe |
Describe an IRF file |
| irf drop |
Drop IRF results from the active IRF file |
| irf graph |
Graph IRFs, dynamic-multiplier functions, and FEVDs |
| irf ograph |
Graph overlaid IRFs, dynamic-multiplier functions, and FEVDs |
| irf rename |
Rename an IRF result in an IRF file |
| irf set |
Set the active IRF file |
| irf table |
Create tables of IRFs, dynamic-multiplier functions, and FEVDs |
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| mgarch |
Multivariate GARCH models |
| mgarch ccc |
Constant conditional correlation multivariate GARCH models |
| mgarch ccc postestimation |
Postestimation tools for mgarch ccc |
| mgarch dcc |
Dynamic conditional correlation multivariate GARCH models |
| mgarch dcc postestimation |
Postestimation tools for mgarch dcc |
| mgarch dvech |
Diagonal vech multivariate GARCH models |
| mgarch dvech postestimation |
Postestimation tools for mgarch dvech |
| mgarch vcc |
Varying conditional correlation multivariate GARCH models |
| mgarch vcc postestimation |
Postestimation tools for mgarch vcc |
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| newey |
Regression with Newey–West standard errors |
| newey postestimation |
Postestimation tools for newey |
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| pergram |
Periodogram |
| pperron |
Phillips–Perron unit-root test |
| prais |
Prais–Winsten and Cochrane–Orcutt regression |
| prais postestimation |
Postestimation tools for prais |
| psdensity |
Parametric spectral density estimation after arima, arfima, and ucm |
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| rolling |
Rolling-window and recursive estimation |
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| sspace |
State-space models |
| sspace postestimation |
Postestimation tools for sspace |
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| tsappend |
Add observations to a time-series dataset |
| tsfill |
Fill in gaps in time variable |
| tsfilter |
Filter a time-series, keeping only selected periodicities |
| tsfilter bk |
Baxter–King time-series filter |
| tsfilter bw |
Butterworth time-series filter |
| tsfilter cf |
Christiano–Fitzgerald time-series filter |
| tsfilter hp |
Hodrick–Prescott time-series filter |
| tsline |
Plot time-series data |
| tsreport |
Report time-series aspects of a dataset or estimation sample |
| tsrevar |
Time-series operator programming command |
| tsset |
Declare data to be time-series data |
| tssmooth |
Smooth and forecast univariate time-series data |
| tssmooth dexponential |
Double-exponential smoothing |
| tssmooth exponential |
Single-exponential smoothing |
| tssmooth hwinters |
Holt–Winters nonseasonal smoothing |
| tssmooth ma |
Moving-average filter |
| tssmooth nl |
Nonlinear filter |
| tssmooth shwinters |
Holt–Winters seasonal smoothing |
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| ucm |
Unobserved-components models |
| ucm postestimation |
Postestimation tools for ucm |
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| var intro (pdf) |
Introduction to vector autoregression models |
| var |
Vector autoregression models |
| var postestimation |
Postestimation tools for var |
| var svar |
Structural vector autoregression models |
| var svar postestimation |
Postestimation tools for svar |
| varbasic |
Fit a simple VAR and graph IRFs or FEVDs |
| varbasic postestimation |
Postestimation tools for varbasic |
| vargranger |
Perform pairwise Granger causality tests after var or svar |
| varlmar |
Perform LM test for residual autocorrelation after var or svar |
| varnorm |
Test for normally distributed disturbances after var or svar |
| varsoc |
Obtain lag-order selection statistics for VARs and VECMs |
| varstable |
Check the stability condition of VAR or SVAR estimates |
| varwle |
Obtain Wald lag-exclusion statistics after var or svar |
| vec intro |
Introduction to vector error-correction models |
| vec |
Vector error-correction models |
| vec postestimation |
Postestimation tools for vec |
| veclmar |
Perform LM test for residual autocorrelation after vec |
| vecnorm |
Test for normally distributed disturbances after vec |
| vecrank |
Estimate the cointegrating rank of a VECM |
| vecstable |
Check the stability condition of VECM estimates |
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| wntestb |
Barlett's periodogram-based test for white noise |
| wntestq |
Portmanteau (Q) test for white noise |
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| xcorr |
Cross-correlogram for bivariate time series |
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| Glossary (pdf) |
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| Subject and author index (pdf) |
