help time
(Note: If you are looking for information on time and date
variables, see [D] dates and times.)
-------------------------------------------------------------------------------
Title
[TS] time series -- Introduction to time-series commands
Description
Some Stata commands are written directly for performing time-series
analyses. This entry provides an index to these commands.
Many other Stata commands allow time-series operators in expressions and
varlists (e.g., regress, summarize, graph, list, ...).
For help with time-series operators and varlists, see tsvarlist.
Before using time-series analysis commands or time-series operators, you
must declare your data to be time series and indicate the time variable.
This is done using the tsset command; see [TS] tsset.
If your interest is in analyzing cross-sectional time-series (panel)
datasets, see [XT] xt.
Data-management tools and time-series operators
tsset Declare data to be time-series data
tsfill Fill in gaps in time variable
tsappend Add observations to a time-series dataset
tsreport Report time-series aspects of a dataset or
estimation sample
tsrevar Time-series operator programming command
haver Load data from Haver Analytics database
rolling Rolling-window and recursive estimation
Univariate time-series
Estimators
arima ARIMA, ARMAX, and other dynamic regression
models
arima postestimation Postestimation tools for arima
arch Autoregressive conditional
heteroskedasticity (ARCH) family of
estimators
arch postestimation Postestimation tools for arch
newey Regression with Newey-West standard errors
newey postestimation Postestimation tools for newey
prais Prais-Winsten and Cochrane-Orcutt regression
prais postestimation Postestimation tools for prais
Time-series smoothers and filters
tssmooth ma Moving-average filter
tssmooth dexponential Double-exponential smoothing
tssmooth exponential Single-exponential smoothing
tssmooth hwinters Holt-Winters nonseasonal smoothing
tssmooth shwinters Holt-Winters seasonal smoothing
tssmooth nl Nonlinear filter
Diagnostic tools
corrgram Tabulate and graph autocorrelations
xcorr Cross-correlogram for bivariate time series
cumsp Cumulative spectral distribution
pergram Periodogram
dfgls DF-GLS unit-root test
dfuller Augmented Dickey-Fuller unit-root test
pperron Phillips-Perron unit-roots test
estat dwatson Durbin-Watson d statistic
estat durbinalt Durbin's alternative test for serial
correlation
estat bgodfrey Breusch-Godfrey test for higher-order serial
correlation
estat archlm Engle's LM test for the presence of
autoregressive conditional
heteroskedasticity
wntestb Bartlett's periodogram-based test for white
noise
wntestq Portmanteau (Q) test for white noise
Multivariate time series
Estimators
var Vector autoregressive models
var postestimation Postestimation tools for var
svar Structural vector autoregressive models
svar postestimation Postestimation tools for svar
varbasic Fit a simple VAR and graph IRFs and FEVDs
varbasic postestimation Postestimation tools for varbasic
vec Vector error-correction models
vec postestimation Postestimation tools for vec
Diagnostic tools
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
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
Forecasting, inference, and interpretation
irf create Obtain IRFs, dynamic-multiplier functions,
and FEVDs
fcast compute Compute dynamic forecasts of dependent
variables after var, svar, or vec
vargranger Perform pairwise Granger causality tests
after var or svar
Graphs and tables
corrgram Tabulate and graph autocorrelations
xcorr Cross-correlogram for bivariate time series
pergram Periodogram
irf graph Graph IRFs, dynamic-multiplier functions,
and FEVDs
irf cgraph Combine graphs of IRFs, dynamic-multiplier
functions, and FEVDs
irf ograph Graph overlaid IRFs, dynamic-multiplier
functions, and FEVDs
irf table Create tables of IRFs, dynamic-multiplier
functions, and FEVDs
irf ctable Combine tables of IRFs, dynamic-multiplier
functions, and FEVDs
fcast graph Graph forecasts of dependent variables
computed by fcast compute
tsline Plot time-series data
tsrline Plot time-series range plot data
varstable Check the stability condition of VAR or SVAR
estimates
vecstable Check the stability condition of VECM
estimates
wntestb Bartlett's periodogram-based test for white
noise
Results management tools
irf add Add IRF results from an IRF file to the
active IRF file
irf describe Describe an IRF file
irf drop Drop IRF results from the active IRF file
irf rename Rename an IRF result in an IRF file
irf set Set the active IRF file
Also see
Manual: [U] 12.5.3 Date and time formats,
[U] 24.3 Displaying dates and times,
[U] 26.14 Models with time-series data,
[TS] intro, [TS] time series
Help: [D] dates and times, [TS] tsset, [U] 11.4 varlists, [XT] xt; and
list above
