得到t检验结果并截取PCR模型的系数

Question

使用PCR时，是否可以获得线性模型系数的t检验统计量？这是一些例子：

> require(pls)
> set.seed (1000)
> pcr_model <- pcr(Sepal.Length~., data = iris, scale = TRUE, validation = "CV")
> coef(pcr_model)
, , 5 comps

                  Sepal.Length
Sepal.Width          0.2161413
Petal.Length         1.4638628
Petal.Width         -0.2402231
Speciesversicolor   -0.3422331
Speciesvirginica    -0.4840979

VS

> summary(lm(Sepal.Length~., data=iris))

Call:
lm(formula = Sepal.Length ~ ., data = iris)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.79424 -0.21874  0.00899  0.20255  0.73103 

Coefficients:
                  Estimate Std. Error t value Pr(>|t|)    
(Intercept)        2.17127    0.27979   7.760 1.43e-12 ***
Sepal.Width        0.49589    0.08607   5.761 4.87e-08 ***
Petal.Length       0.82924    0.06853  12.101  < 2e-16 ***
Petal.Width       -0.31516    0.15120  -2.084  0.03889 *  
Speciesversicolor -0.72356    0.24017  -3.013  0.00306 ** 
Speciesvirginica  -1.02350    0.33373  -3.067  0.00258 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.3068 on 144 degrees of freedom
Multiple R-squared:  0.8673,    Adjusted R-squared:  0.8627 
F-statistic: 188.3 on 5 and 144 DF,  p-value: < 2.2e-16

或者我需要自己计算它们吗？ 此外，模型的截距值在哪里？