How do I get RSS from a linear model output

Here are some ways of computing the residual sum of squares (RSS) using the built-in anscombe data set:

fm <- lm(y1 ~ x1+x2+x3, anscombe)

deviance(fm)
## [1] 13.76269

sum(resid(fm)^2)
## [1] 13.76269

anova(fm) # see the Residuals row of the Sum Sq column
## Analysis of Variance Table
##
## Response: y1
##           Df Sum Sq Mean Sq F value  Pr(>F)   
## x1         1 27.510 27.5100   17.99 0.00217 **
## Residuals  9 13.763  1.5292                   
## ---
## Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

anova(fm)["Residuals", "Sum Sq"]
## [1] 13.76269

with(summary(fm), df[2] * sigma^2)
## [1] 13.76269

Regarding the last one, note that summary(fm)$df[2] and summary(fm)$sigma are shown in the summary(fm) output in case you want to calculate RSS using only a printout from summary. In particular, for the output shown in the question df[2] = 116 and sigma = 1.928 so RSS = df[2] * sigma^2 = 116 * 1.928^2 = 431.1933 .