r - 比较回归模型与 R

Question

中是否有可用的工具？电话 生成可发表的回归表？我正在写一篇类(class)论文，我需要在其中比较几个回归模型，如果我能让它们嵌套在像 this one 这样的单个表中，我会很高兴。 ，来自 estout斯塔塔包。

我查了 xtable ，但无法达到相同的结果。任何提示将不胜感激。

这是我的想法:

Answer 1

您可能想要 mtable 'memic' 包中的函数。它具有关联的 LaTeX 输出参数:

==========================================================================
                                              Model 1   Model 2   Model 3 
--------------------------------------------------------------------------
Constant                                     30.628***  6.360*** 28.566***
                                             (7.409)   (1.252)   (7.355)  
Percentage of population under 15            -0.471**            -0.461** 
                                             (0.147)             (0.145)  
Percentage of population over 75             -1.934              -1.691   
                                             (1.041)             (1.084)  
Real per-capita disposable income                       0.001    -0.000   
                                                       (0.001)   (0.001)  
Growth rate of real per-capita disp. income             0.529*    0.410*  
                                                       (0.210)   (0.196)  
--------------------------------------------------------------------------
sigma                                          3.931     4.189     3.803  
R-squared                                      0.262     0.162     0.338  
F                                              8.332     4.528     5.756  
p                                              0.001     0.016     0.001  
N                                             50        50        50      
==========================================================================

这是你得到的 LaTeX 代码:

texfile123 <- "mtable123.tex"
write.mtable(mtable123,forLaTeX=TRUE,file=texfile123)
file.show(texfile123)
#------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Calls:
% Model 1:  lm(formula = sr ~ pop15 + pop75, data = LifeCycleSavings) 
% Model 2:  lm(formula = sr ~ dpi + ddpi, data = LifeCycleSavings) 
% Model 3:  lm(formula = sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings) 
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{tabular}{lcD{.}{.}{7}cD{.}{.}{7}cD{.}{.}{7}}
\toprule
&&\multicolumn{1}{c}{Model 1} && \multicolumn{1}{c}{Model 2} && \multicolumn{1}{c}{Model 3}\\
\midrule
Constant                                    &  & 30.628^{***} &&  6.360^{***} && 28.566^{***}\\
                                            &  &  (7.409)     &&  (1.252)     &&  (7.355)    \\
Percentage of population under 15           &  & -0.471^{**}  &&              && -0.461^{**} \\
                                            &  &  (0.147)     &&              &&  (0.145)    \\
Percentage of population over 75            &  &  -1.934      &&              &&  -1.691     \\
                                            &  &  (1.041)     &&              &&  (1.084)    \\
Real per-capita disposable income           &  &              &&   0.001      &&  -0.000     \\
                                            &  &              &&  (0.001)     &&  (0.001)    \\
Growth rate of real per-capita disp. income &  &              &&  0.529^{*}   &&  0.410^{*}  \\
                                            &  &              &&  (0.210)     &&  (0.196)    \\
\midrule
sigma                                       &  &     3.931    &&     4.189    &&     3.803   \\
R-squared                                   &  &     0.262    &&     0.162    &&     0.338   \\
F                                           &  &     8.332    &&     4.528    &&     5.756   \\
p                                           &  &     0.001    &&     0.016    &&     0.001   \\
N                                           &  &    50        &&    50        &&    50       \\
\bottomrule
\end{tabular}