解决方案:用set seed设定种子,设定种子之后相当于是给随机数一个初始值,每次使用相同随机数种子的结果便会相同。 例如下面这两段过程,在没有用set seed设定种子之前,同样的代码生成的变量却不一样。 clear all set obs 100 Number ofobservations(_N) was 0, now 100. gen x=runiform() sum Variable | Obs...
Number of observations = 100 Notes: Using analytical PMPs. Result bmareg_inf has the smallest mean LPS. 信息更丰富的 bmareg_inf 模型的平均 LPS 稍小,但所有模型的 LPS 摘要非常相似。 ▋清理 我们在分析过程中生成了多个数据集。我们不再需要它们,所以我们最后删除它们。但您可能决定保留它们,特别是当...
Number of observations N = 758Number of regressors K = 13Number of endogenous regressors K1 = 1Number of instruments L = 16Number of excluded instruments L1 = 4 IV (2SLS) estimation--- Estimates efficient for homoskedasticity onlyStatistics consistent for homoskedasticity only Number of obs = 75...
Number of observations N = 758Number of regressors K = 13Number of endogenous regressors K1 = 1Number of instruments L = 16Number of excluded instruments L1 = 4 IV (2SLS) estimation--- Estimates efficient for homoskedasticity onlyStatistics consistent for homoskedasticity only Number of obs = 75...
minobs specifies the minimum number of observations in each of the regimes when searching for r_hats. The default is 10. 案例介绍1 xtthres tobin size tang prof, th(grow) d(tl) xtthres tobin size tang prof, th(grow) d(tl) bs2(200) bs3(100) minobs(30) ...
alpha(real) specifies critical valueforcalculation of optimal bandwidth threshold(real) specifies cutoff valueforthetest qobs(real) specifies# of observations closest to cutoff --- 具体表示为:alpha(real) 指定计算最优带宽的临界值 Threshold (real)指定测试的截止值 qobs(real)指定最接近...
Number of observationsinthe DIFF-IN-DIFF: 70 Before After Control: 16 24 40 Treated: 12 18 30 28 42 --- Outcome var. | y | S. Err. | |t| | P>|t| ---+---+---+---+--- Before | | | | Control | 3.6e+08| | | Treated...
//将设定一个观察值 . set obs 1 number of observations (_N) was 0, now 1 //提示信息说,之前系统中没有观察单位,现在有了一个 . gen a=1 . d /*d 为 describ 命令的略写,describ 命令显示数据集的 属性信息,注意观察显示结果中,a 的 storage type 为 float 型, 浮点型为默认类型*/ Contains...
S458785 XAUTO: Stata module to input an extended version of the auto data byRoger Newson S458784 VARDISTINCT: Stata module to generate a variable representing the number(s) of distinct observations or values byHarrison Garrett S458783 QRKD: Stata module to estimate and produce robust inference ...
S458897 KOTLARSKI: Stata module to execute deconvolution kernel density estimation and produce a robust construction of its uniform confidence band by Kengo Kato & Yuya Sasaki & Takuya Ura S458896 TESENSITIVITY: Stata module for assessing sensitivity to the unconfoundedness assumption ...