Có 200+ tài liệu thuộc chủ đề "Hướng dẫn sử dụng SAS / ETS"
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print covariances of the parameter estimates MODEL COVB. print the inverse of the crossproducts matrix MODEL I. specify the endogenous variables ENDOGENOUS specify instrumental variables INSTRUMENTS write predicted and residual values to a data set OUTPUT. PROC SYSLIN Statement. PROC SYSLIN options. The following options can be used with the PROC SYSLIN statement.. Data Set Options. DATA=SAS-data-set. specifies the input...
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1792 F Chapter 27: The SYSLIN Procedure. Parameters are referred to as label.variable, where label is the model label and variable is the name of the regressor to which the parameter is attached. (If the MODEL statement does not have a label, you can use the dependent variable name as the label for the model, provided the dependent variable uniquely...
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The SDIAG option in the PROC SYSLIN statement computes estimates by assuming uncorrelated errors across equations. The OVERID option in the MODEL statement can be used to test for overidentifying restrictions on parameters of each equation. The alternative hypothesis is that at least one of the assumed zero coefficients is nonzero. The formula for the test is given as follows....
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Output 27.1.4 The OUTEST= Data Set. proc syslin data=klein 3sls reduced;. The 3SLS estimates are shown in Output 27.1.5 through Output 27.1.7. The reduced form estimates are shown in Output 27.1.8 through Output 27.1.11.. Output 27.1.5 3SLS Estimates for Consumption. Output 27.1.5 continued. Output 27.1.6 3SLS Estimates for Investments. plag Profits Lagged klag lt;.0001 Capital Stock Lagged. Output 27.1.7 3SLS...
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(1960), “On Finite Sample Distributions of Generalized Classical Linear Identifiability Test Statistics,” Journal of the American Statistical Association . (1977), “Some Properties of a Modification of the Limited Information Estimator,”. (1982), “Some Sampling Properties of Minimum Expected Loss (MELO) Estimators of Structural Coefficients,” Journal of the Econometrics . (1962), “An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for...
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1832 F Chapter 28: The TIMEID Procedure (Experimental). Figure 28.1 Time ID Decomposition. The count-based frequency distributions summarize features of the time ID variable. Individual printed and plotted outputs are available to describe the distribution of the number of spans, offsets, and interval counts that occur in the time ID variable. Figure 28.2 illustrates a count-based frequency distribution of the...
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Output 28.1.6 Time ID Offsets Histogram. The span diagnostics Output 28.1.7 and Output 28.1.8 show the distribution of the span sizes between successive DATE values. The TriWeek data set has three different span sizes of widths 0, 1 and 2.. Output 28.1.7 Time ID Span Listings. Output 28.1.7 continued. Output 28.1.8 Time ID Span Histogram. Output 28.1.9 and Output 28.1.10...
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proc timeseries data=transactions out=timeseries;. The OUT=TIMESERIES option specifies that the resulting time series data for each customer is to be stored in the data set WORK.TIMESERIES . After the transactional data is accumulated into a time series format, many of the procedures provided with SAS/ETS software can be used to analyze the resulting time series data.. The OUTEST=ESTIMATES data set...
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The following options can be specified in the CORR statement following the slash. specifies the number of lags to be stored in the OUTCORR= data set or to be plotted. The default is 24 or three times the length of the seasonal cycle, whichever is smaller. specifies the number of parameters used in the model that created the residual time...
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By default, the first group contains the principal components whose contribution to variability in the series sums to greater than the THRESHOLDPCT= value of 90%, and the second group contains the remaining components.. specifies the window length to be used in the analysis. It represents the maximum lag used in the SSA autocovariance calculations. When the SEASONALITY= option is provided...
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1882 F Chapter 29: The TIMESERIES Procedure. ADD centered moving average of O t. LOGADD centered moving average of log.O t / PSEUDOADD centered moving average of O t. LOGADD SA t D O t =exp.S t / D exp.T C t C I t / PSEUDOADD SA t D T C t I t. Correlation Analysis. Correlation analysis can...
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1892 F Chapter 29: The TIMESERIES Procedure. The preceding correlation statistics are computed for each specified time lag.. When the CORR statement TRANSPOSE=YES option is specified, the variable values are related to correlation statistics specified in the CORR statement and the variable names are related to the NLAG= or LAGS= options.. _NAME_ variable name. _STAT_ correlation statistic name _LABEL_ correlation...
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The following statements use the EXPAND procedure to smooth the analysis variable named STOREITEM. The smoothed series are stored in the data set WORK.SMOOTHED. If the time ID variable TIMESTAMP contains SAS datetime values instead of SAS date values, the INTERVAL=, START=, and END= options must be changed accordingly and the following statements could be used:. The monthly time series...
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Output 29.4.1 Period Plot. Output 29.4.2 Frequency Plot. Example 29.5: Illustration of Singular Spectrum Analysis. The following statements extract two additive components from the SASHELP.AIR time series by using the THRESHOLDPCT= option to specify that the first component represent 80% of the variability in the series. The resulting groupings, consisting of the first three and remaining nine singular value components,...
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1922 F Chapter 30: The TSCSREG Procedure. proportion of the transformed sum of squares of the dependent variable that is attributable to the influence of the independent variables. In the case of OLS estimation, the Buse R-square measure is equivalent to the usual R-square measure.. The actual estimation of the fixed-effects models is not LSDV. In the first step, the...
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The UCM Procedure. Overview: UCM Procedure. Getting Started: UCM Procedure. Syntax: UCM Procedure. Details: UCM Procedure. 1934 F Chapter 31: The UCM Procedure. Examples: UCM Procedure. Example 31.1: The Airline Series Revisited. Example 31.2: Variable Star Data. Example 31.3: Modeling Long Seasonal Patterns. Example 31.4: Modeling Time-Varying Regression Effects. Example 31.5: Trend Removal Using the Hodrick-Prescott Filter. Example 31.6: Using...
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1942 F Chapter 31: The UCM Procedure. Figure 31.7 Smoothed Trend plus Seasonal in the Logair Series. The UCM procedure uses the following statements:. PROC UCM <. The PROC UCM and MODEL statements are required. The statements and options controlling the UCM procedure are summarized in the following table.. You can use the PRINT= and PLOT= options in the individual...
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requests the printing of the filtered or smoothed estimate of the block seasonal component t . specifies the type of the block seasonal component. specifies an initial value for the disturbance variance. 2 , in the t equation at the start of the parameter estimation process. A BY statement can be used in the UCM procedure to process a data...
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It also fixes the coefficient of the first-order seasonal moving average polynomial to 0.1. lists the starting values of the coefficients of the nonseasonal autoregressive polynomial .B/ D 1 1 B. where the order p is specified in the P= option. lists the starting values of the coefficients of the nonseasonal moving average polynomial .B/ D 1 1 B. where...
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specifies the degree of the spline. It can be any integer greater than or equal to zero. This list of values must be a nondecreasing sequence of integers within the range of 2 to .s 1/, where s is the season length specified in the LENGTH= option. The length can be any integer greater than or equal to three.. fixes...