Stata Bookstore: Time-Series Reference Manual, Release 10

intro (pdf)	Introduction to time-series manual

time series (pdf)	Introduction to time-series commands

arch	Autoregressive conditional heteroskedasticity (ARCH) family of estimators
arch postestimation	Postestimation tools for arch
arima (pdf)	ARIMA, ARMAX, and other dynamic regression models
arima postestimation	Postestimation tools for arima

corrgram (pdf)	Tabulate and graph autocorrelations
cumsp	Cumulative spectral distribution

dfgls	DF-GLS unit-root test
dfuller	Augmented Dickey–Fuller unit-root test

estimation options	Estimation options

fcast compute	Compute dynamic forecasts of dependent variables after var, svar, or vec
fcast graph	Graph forecasts of dependent variables computed by fcast compute

haver	Load data from Haver Analytics database

irf	Create and analyze IRFs, dynamic-multiplier functions, and FEVDs
irf add	Add IRF 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

newey	Regression with Newey–West standard errors
newey postestimation	Postestimation tools for newey

pergram	Periodogram
pperron	Phillips–Perron unit-root test
prais	Prais–Winsten regression and Cochrane–Orcutt regression
prais postestimation	Postestimation tools for prais

rolling	Rolling window and recursive estimation

tsappend	Add observations to a time-series dataset
tsfill	Fill in missing times with missing observations in time-series data
tsline	Plot time-series data
tsreport	Report time-series aspects of a dataset or estimation sample
tsrevar	Time-series operator programming command
tsset	Declare a dataset 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

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
varbasic postestimation	Postestimation tools for varbasic
vargranger	Perform pairwise Granger causality tests after var or svar
varlmar	Obtain LM statistics 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	Obtain LM statistics for residual autocorrelation after vec
vecnorm	Test for normally distributed disturbances after vec
vecrank	Estimate the cointegrating rank using Johansen's framework
vecstable	Check the stability condition of VECM estimates

wntestb	Barlett's periodogram-based test for white noise
wntestq	Portmanteau (Q) test for white noise

xcorr	Cross-correlogram for bivariate time series

glossary	Glossary of terms

Subject and author index (pdf)

Time-Series Reference Manual

Table of contents