Có 160+ tài liệu thuộc chủ đề "Hướng dẫn sử dụng SAS / ETS"
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1382 F Chapter 19: The PANEL Procedure. Output 19.2.6 Diagnostic Panel 2. The graph shown in Output 19.2.7 shows a detail plot of residuals by cross section. proc panel data=airline;. model lC = lQ lPF LF / fixtwo plots(unpack only. Output 19.2.7 Surface Plot of the Residual. Example 19.3: The Airline Cost Data: Further Analysis. Using the same data as...
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(1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” The Review of Economic Studies . Journal of Econometrics . (1994), “Incomplete Panels: A Comparative Study of Alternative Esti- mators for the Unbalanced One-Way Error Component Regression Model,” Journal of Econometrics . H., Song, Seuck H., and Jung, Byoung C. (2002), “A Comparative...
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1402 F Chapter 20: The PDLREG Procedure. A BY statement can be used with PROC PDLREG to obtain separate analyses on observations in groups defined by the BY variables.. MODEL Statement. The MODEL statement specifies the regression model. The keyword MODEL is followed by the dependent variable name, an equal sign, and a list of independent effects. Every variable in...
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1412 F Chapter 20: The PDLREG Procedure. The printed output produced by the PDLREG procedure is shown in Output 20.1.1. Output 20.1.1 Printed Output Produced by PROC PDLREG. The PDLREG Procedure Dependent Variable ce Ordinary Least Squares Estimates. Output 20.1.1 continued. model ce = q1 q2 q3 ca ca_1 ca_2 ca_3 ca_4 ca_5;. restrict - ca + 5*ca_1 - 10*ca_2...
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1422 F Chapter 21: The QLIM Procedure. Example 21.2: Tobit Analysis. 1469 Example 21.3: Bivariate Probit Analysis. 1471 Example 21.4: Sample Selection Model. 1472 Example 21.5: Sample Selection Model with Truncation and Censoring. 1473 Example 21.6: Types of Tobit Models. 1476 Example 21.7: Stochastic Frontier Models. Overview: QLIM Procedure. The QLIM (qualitative and limited dependent variable model) procedure analyzes univariate...
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1432 F Chapter 21: The QLIM Procedure. OP specifies the covariance from the outer product matrix.. HESSIAN specifies the covariance from the inverse Hessian matrix.. QML specifies the covariance from the outer product and Hessian matrices (the quasi-maximum likelihood estimates).. specifies the number of draws for Monte Carlo integration.. specifies the optimization method. Valid values are as follows:. BOUNDS Statement....
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1442 F Chapter 21: The QLIM Procedure. Each parameter reference should be preceded by the name of the dependent variable of the particular model and the dot sign. in the system of equations. Tests expressions can be composed only of algebraic operations involving the addition symbol. The TEST statement accepts labels that are reproduced in the printed output. TEST statement...
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1452 F Chapter 21: The QLIM Procedure. The normal-truncated normal model is a generalization of the normal-half normal model by allowing the mean of u i to differ from zero. The joint density of v i and u i can be written as. v 2 2 v 2 The marginal density function of for the production function is f. and...
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1462 F Chapter 21: The QLIM Procedure. The second version of the estimate (Jondrow et al., 1982) is TE2 i D exp f E.u i j i / g. Hence, f .u j / is the density for N C. The second version of the estimate is TE2 i D exp f E.u i j i / g where. OUTEST=...
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Output 21.3.1 Bivariate Probit Analysis Results. Number of Endogenous Variables 2. Number of Observations 500. Maximum Absolute Gradient 3.23363E-7. Number of Iterations 17. y1.Intercept lt;.0001. y1.x lt;.0001. y2.Intercept lt;.0001. y2.x lt;.0001. Example 21.4: Sample Selection Model. Sample Selection. proc qlim data=mroz;. The output of the QLIM procedure is shown in Output 21.4.1.. Output 21.4.1 Sample Selection. Number of Observations 753....
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Example 21.7: Stochastic Frontier Models. This example illustrates the estimation of stochastic frontier production and cost models.. title1 'Stochastic Frontier Production Model';. The following statements estimate a stochastic frontier exponential production model that uses Christensen Associates data:. Stochastic Frontier Production Model. Figure 21.7.1 shows the results from this production model.. Output 21.7.1 Stochastic Frontier Production Model. Stochastic Frontier Production Model...
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1492 F Chapter 22: The SEVERITY Procedure (Experimental). Overview: SEVERITY Procedure. The SEVERITY procedure estimates parameters of any arbitrary continuous probability distribution that is used to model magnitude (severity) of a continuous-valued event of interest. PROC SEVERITY is especially useful when the severity of an event does not follow typical distributions, such as the normal distribution, that are often assumed...
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1502 F Chapter 22: The SEVERITY Procedure (Experimental). Figure 22.9 P-P Plots for the Lognormal and Weibull Models Fitted to Truncated and Censored Data. Figure 22.9 continued. For the current example, Figure 22.10 shows the initial values that are obtained by the predefined method for the Burr distribution. It also shows the summary of the optimization process and the final...
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OUTCDF=SAS-data-set. names the output data set to contain estimates of the cumulative distribution function (CDF) value at each of the observations. The data set also contains the estimates of the empirical distribution function (EDF). Details of the variables in this data set are provided in the section “OUTCDF= Data Set” on page 1555.. OUTMODELINFO=SAS-data-set. names the output data set to...
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Sequence and type of arguments:. x Numeric value of the random variable at which the PDF value should be evaluated p1 Numeric value of the first parameter. p2 Numeric value of the second parameter. pm Numeric value of the mth parameter. Return value: Numeric value that contains the PDF value f .x I p 1 . In other words, if...
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Given n observations of the severity value y i (1 i n), the estimate of kth raw moment is denoted by m k and computed as. PROC SEVERITY uses the following practical method of computing p . Let y p and y p C denote two consecutive values in the array of y values such that F .y O p...
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Given this, the likelihood of the data L is as follows:. Some aspects of the optimization process can be controlled by using the NLOPTIONS statement.. Thus, following the notation of the section “Likelihood Function” on page 1541, the likelihood of the data is as follows:. Note that the likelihood of the observations that are not left-truncated (observations in sets E...
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In the interval ŒZ i 1 . Using the probability integral transform z D F .y/, the formula simplifies to AD D N. CvM The Cramér-von-Mises (CvM) statistic is a quadratic EDF statistic that is proportional to the expected value of the squared difference between the EDF and CDF. Using the probability integral transform z D F .y/, the formula...
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1562 F Chapter 22: The SEVERITY Procedure (Experimental). If left-truncation is specified and the MARKTRUNCATED option is specified, then the left-truncated observations are marked in the plot. If right-censoring is specified and the MARKCENSORED option is specified, then the right-censored observations are marked in the plot.. If regressor variables are specified, then the plotted CDF estimates are from a mixture...
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1572 F Chapter 22: The SEVERITY Procedure (Experimental). The results shown in Output 22.2.3 indicate that the Burr distribution has now converged and that the Burr and Weibull distributions have an almost identical fit for the data. The NORMAL_S distribution is still the best distribution according to the likelihood-based criteria.. Output 22.2.3 Summary of Results after Changing Maximum Number of...