stata中如何先生成一个变量的中值,再根据这个中值进行分组生成虚拟变量,大于等于中值的取值为1,否//第一反应代码如下: egen loan_ratio_med = medium(loan_ratio) //但是这样做会报错: unknown egen function medium() //正确的做法是: egen x_p50 = pctile(x), p(50)stata怎么求指定 ...
stata中如何先生成一个变量的中值,再根据这个中值进行分组生成虚拟变量,大于等于中值的取值为1,否//第一反应代码如下: egen loan_ratio_med = medium(loan_ratio) //但是这样做会报错: unknown egen function medium() //正确的做法是: egen x_p50 = pctile(x), p(50)stata怎么求指定 ...
Unknown break point Known break points Cumulative sum test for stability of coefficients ARCH LM test Moran's test for spatial dependence Diagnostic plots Added variable (leverage) plot Component plus residual plot Leverage vs. squared residual plot Residual vs. fitted plot Residual vs. pred...
S456956 PAVERAGE: Stata module to calculate p-period-average series in a panel dataset byP. Wilner Jeanty S456955 WDIRESHAPE: Stata module to reshape World Development Indicators database byP. Wilner Jeanty S456954 METACUM: Stata module to perform cumulative meta-analysis, with graphics byRoss...
In series estimation, the unknown mean function is approximated by a linear combination of elements in the basis function. For instance, we can consider a polynomial basis. We can approximate the unknown mean function using a polynomial. The more complex the mean function, the more polynomial ...
qhapipf Module to perform analysis of quantitative traits using regression and log-linear modelling when PHASE is unknown qic Module to compute model selection criterion in GEE analyses qll Module to implement Elliott-M��ller efficient test for general persistent time variation in regression coef...
A plotting functioncplot()to provide the commonly needed visual summaries of predictions or average marginal effects conditional on a covariate. Apersp()method for "lm", "glm", and "loess" objects to provide three-dimensional representations of response surfaces or marginal effects over two covariat...
These plots are derived either to approximate the regression function with local sample averages of the outcome variable within bins of the running variable or to depict the overall variability of the data in a disciplined and objective way. These selectors are obtained by appr 17、oximating the...
In an empirical setting this implies that 1) the unknown number of unobserved common factors has to be equal or larger than the rank of the unobserved average factor loadings; 2) cross-section averages with a zero loading can pose a problem if the number of cross-section averages is small...
qhapipf Module to perform analysis of quantitative traits using regression and log-linear modelling when PHASE is unknown qic Module to compute model selection criterion in GEE analyses qll Module to implement Elliott-M��ller efficient test for general persistent time variation in regression coef...