2016-08-19 73 views
1

我在R中使用stargazer包进行回归输出。我有一个自定义的估计过程,它不会产生模型对象,而只会产生系数和标准错误的向量。有没有一种方法可以将这些提供给stargazer并获得格式良好的输出表?stargazer - 用户提供的系数和SE

例子:

dep.var <- "foo" 
regressors <- c("bar", "baz", "xyz") 
vec.coeffs <- c(1.2, 2.3, 3.4) 
vec.se <- c(0.1, 0.1, 0.3) 

输出应该类似于:

=============================================== 
         Dependent variable:  
        --------------------------- 
           foo    
----------------------------------------------- 
bar       1.200***     
           (0.100)   

baz       2.300***   
           (0.100) 

xyz       3.400***   
           (0.300)   

----------------------------------------------- 

回答

2

这里有一个建议:主要的想法是做一个假lm对象,然后应用自定义系数,社会企业等。到stargazer输出:

d <- as.data.frame(matrix(rnorm(10 * 4), nc = 4)) 
names(d) <- c(dep.var, regressors) 
f <- as.formula(paste(dep.var, "~ 0 +", paste(regressors, collapse = "+"))) 
p <- lm(f, d) 

stargazer(p, type = "text", 
    coef = list(vec.coeffs), 
    se = list(vec.se), 
    t = list(vec.coeffs/vec.se), 
    omit.stat = "all") 
# ================================= 
#   Dependent variable:  
#  --------------------------- 
#     foo    
# --------------------------------- 
# bar   1.200***   
#     (0.100)   

# baz   2.300***   
#     (0.100)   

# xyz   3.400***   
#     (0.300)   

# ================================= 
# ================================= 
# Note: *p<0.1; **p<0.05; ***p<0.01