R中的回归(vs Eviews)

Question

当您在Eviews中进行回归时,您会获得如下统计信息的面板:

在R中是否有一种方法可以在一个列表中获得关于R中的回归的所有/大部分统计数据？

Answer 1

请参阅summary,它将为大多数类的回归对象生成摘要.

例如,来自help(glm):

> clotting <- data.frame(
+          u = c(5,10,15,20,30,40,60,80,100),
+          lot1 = c(118,58,42,35,27,25,21,19,18),
+          lot2 = c(69,35,26,21,18,16,13,12,12))
>      summary(glm(lot1 ~ log(u), data = clotting, family = Gamma))

Call:
glm(formula = lot1 ~ log(u), family = Gamma, data = clotting)

Deviance Residuals: 
     Min        1Q    Median        3Q       Max  
-0.04008  -0.03756  -0.02637   0.02905   0.08641  

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.0165544  0.0009275  -17.85 4.28e-07 ***
log(u)       0.0153431  0.0004150   36.98 2.75e-09 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for Gamma family taken to be 0.002446059)

    Null deviance: 3.51283  on 8  degrees of freedom
Residual deviance: 0.01673  on 7  degrees of freedom
AIC: 37.99

Number of Fisher Scoring iterations: 3

R对GUI程序的重大胜利通常是函数的输出可用.所以你可以这样做:

> s =  summary(glm(lot1 ~ log(u), data = clotting, family = Gamma))
> s$coefficients[1,]
     Estimate    Std. Error       t value      Pr(>|t|) 
-1.655438e-02  9.275466e-04 -1.784749e+01  4.279149e-07 
> s$cov.scaled
              (Intercept)        log(u)
(Intercept)  8.603427e-07 -3.606457e-07
log(u)      -3.606457e-07  1.721915e-07

获取t和p以及参数或缩放协方差矩阵的所有内容.但是,请务必阅读摘要方法的文档,以确保获得您认为的结果.有时返回对象中的事物可以在变换后的尺度上计算,并且在打印对象时呈现在未变换的尺度上.

但请注意,您似乎作为示例显示的是ARIMA模型,并且R中的对象没有很好的summary功能arima:

> m = arima(lh, order = c(1,0,1))
> summary(m)
          Length Class  Mode     
coef       3     -none- numeric  
sigma2     1     -none- numeric  
var.coef   9     -none- numeric  
mask       3     -none- logical  
loglik     1     -none- numeric  
aic        1     -none- numeric  
arma       7     -none- numeric  
residuals 48     ts     numeric  
call       3     -none- call     
series     1     -none- character
code       1     -none- numeric  
n.cond     1     -none- numeric  
model     10     -none- list     

这只是包含这些元素的列表对象的默认摘要.只需打印它就可以获得以下几点:

> m

Call:
arima(x = lh, order = c(1, 0, 1))

Coefficients:
         ar1     ma1  intercept
      0.4522  0.1982     2.4101
s.e.  0.1769  0.1705     0.1358

sigma^2 estimated as 0.1923:  log likelihood = -28.76,  aic = 65.52