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2007-12-23

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Time-Series Reference Manual, Release 10

Table of contents
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)

[此贴子已经被作者于2007-12-23 9:33:52编辑过]

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2007-12-23 23:20:00
支持,谢谢
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2007-12-24 00:15:00
我也来谢谢,很好的书
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2007-12-24 00:59:00
提示: 作者被禁止或删除 内容自动屏蔽
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2007-12-24 08:56:00
感谢!!!
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2007-12-24 10:17:00

多谢楼主

收下了!

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