> 
> x_red <- rep(1,length(y))
> 
> abt.full <- lm(y ~ -1+x1+x2+x3+x4+x5, weights=wt)
> summary(abt.full)

Call:
lm(formula = y ~ -1 + x1 + x2 + x3 + x4 + x5, weights = wt)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.69801 -0.66836  0.01743  0.52187  1.74933 

Coefficients:
   Estimate Std. Error t value Pr(>|t|)    
x1  15.4200     0.4375   35.24   <2e-16 ***
x2  18.5275     0.4430   41.82   <2e-16 ***
x3  15.0037     0.8785   17.08   <2e-16 ***
x4   9.7412     0.2888   33.73   <2e-16 ***
x5  12.3400     0.2721   45.36   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 1 on 35 degrees of freedom
Multiple R-squared: 0.9946,     Adjusted R-squared: 0.9939 
F-statistic:  1296 on 5 and 35 DF,  p-value: < 2.2e-16 

> anova(abt.full)
Analysis of Variance Table

Response: y
          Df  Sum Sq Mean Sq F value    Pr(>F)    
x1         1 1242.14 1242.14 1241.98 < 2.2e-16 ***
x2         1 1749.30 1749.30 1749.06 < 2.2e-16 ***
x3         1  291.75  291.75  291.71 < 2.2e-16 ***
x4         1 1137.94 1137.94 1137.79 < 2.2e-16 ***
x5         1 2057.55 2057.55 2057.27 < 2.2e-16 ***
Residuals 35   35.00    1.00                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> abt.red <- lm(y ~ -1+x_red, weights=wt)
> summary(abt.red)

Call:
lm(formula = y ~ -1 + x_red, weights = wt)

Residuals:
    Min      1Q  Median      3Q     Max 
-5.2479 -1.3111  0.9216  2.6573  5.7813 

Coefficients:
      Estimate Std. Error t value Pr(>|t|)    
x_red  12.8764     0.4981   25.85   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 3.035 on 39 degrees of freedom
Multiple R-squared: 0.9449,     Adjusted R-squared: 0.9434 
F-statistic: 668.3 on 1 and 39 DF,  p-value: < 2.2e-16 

> anova(abt.red)
Analysis of Variance Table

Response: y
          Df Sum Sq Mean Sq F value    Pr(>F)    
x_red      1 6154.5  6154.5  668.28 < 2.2e-16 ***
Residuals 39  359.2     9.2                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> anova(abt.red,abt.full)
Analysis of Variance Table

Model 1: y ~ -1 + x_red
Model 2: y ~ -1 + x1 + x2 + x3 + x4 + x5
  Res.Df    RSS Df Sum of Sq     F    Pr(>F)    
1     39 359.17                                 
2     35  35.00  4    324.16 81.03 < 2.2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
>