basics.sagews

R Basics

Just a demo, how R can be called from Sage to do something useful.

%r
x <- c(1,4,3,4,3,2,3,2,3,6,3)
summary(x)

Min. 1st Qu. Median Mean 3rd Qu. Max. 1.000 2.500 3.000 3.091 3.500 6.000

%r
x[1]
x[2]

1

4

%r
z <- sample(-5:5, 30, replace=T)
z
summary(z)

1. 2
2. 0
3. -5
4. 2
5. -2
6. 1
7. 2
8. 1
9. -2
10. 0
11. 1
12. -5
13. 4
14. 0
15. -5
16. 4
17. 0
18. -2
19. -3
20. 2
21. 0
22. -3
23. 3
24. -4
25. 0
26. 2
27. -5
28. 3
29. 1
30. 0

Min. 1st Qu. Median Mean 3rd Qu. Max. -5.0000 -2.0000 0.0000 -0.2667 2.0000 4.0000

%r
plot(-5:5, sample(-5:5, 11, replace=F))

Linear Regression

%r
X <- sort(runif(100, -5,5))
Y <- -2 + 1.1 * X + rnorm(100, 0, 5)
lmobj <- lm(Y ~ X)
summary(lmobj)

Call: lm(formula = Y ~ X) Residuals: Min 1Q Median 3Q Max -10.8981 -2.7457 0.1564 2.8784 11.6248 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.6343 0.4371 -3.739 0.000311 *** X 0.8292 0.1447 5.730 1.11e-07 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 4.355 on 98 degrees of freedom Multiple R-squared: 0.2509, Adjusted R-squared: 0.2433 F-statistic: 32.83 on 1 and 98 DF, p-value: 1.11e-07