load("~/Dropbox/enseignement/ml/Lectures/rmds/prostate.rda")
names(prostate)
## [1] "lcavol" "lweight" "age" "lbph" "svi" "lcp" "gleason"
## [8] "pgg45" "lpsa"
head(prostate)
## lcavol lweight age lbph svi lcp gleason pgg45 lpsa
## 1 -0.5798185 2.769459 50 -1.386294 0 -1.386294 6 0 -0.4307829
## 2 -0.9942523 3.319626 58 -1.386294 0 -1.386294 6 0 -0.1625189
## 3 -0.5108256 2.691243 74 -1.386294 0 -1.386294 7 20 -0.1625189
## 4 -1.2039728 3.282789 58 -1.386294 0 -1.386294 6 0 -0.1625189
## 5 0.7514161 3.432373 62 -1.386294 0 -1.386294 6 0 0.3715636
## 6 -1.0498221 3.228826 50 -1.386294 0 -1.386294 6 0 0.7654678
dim(prostate)
## [1] 97 9
lm.fit <- lm(lpsa~lcavol, data=prostate)
summary(lm.fit)
##
## Call:
## lm(formula = lpsa ~ lcavol, data = prostate)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.67624 -0.41648 0.09859 0.50709 1.89672
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.50730 0.12194 12.36 <2e-16 ***
## lcavol 0.71932 0.06819 10.55 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7875 on 95 degrees of freedom
## Multiple R-squared: 0.5394, Adjusted R-squared: 0.5346
## F-statistic: 111.3 on 1 and 95 DF, p-value: < 2.2e-16
attach(prostate)
plot(lcavol, lpsa, col="red")
abline(lm.fit, lwd=3, col="blue")
coef(lm.fit)
## (Intercept) lcavol
## 1.5072975 0.7193204
confint(lm.fit)
## 2.5 % 97.5 %
## (Intercept) 1.2652222 1.7493727
## lcavol 0.5839404 0.8547004