#### "All the examples" from ./R-intro.texi #### -- in a way that this should be(come) an executable script. options(digits=5, width=65)##--- for outputs ! ## 2. Simple Manipulations x <- c(10.4, 5.6, 3.1, 6.4, 21.7) assign("x", c(10.4, 5.6, 3.1, 6.4, 21.7)) c(10.4, 5.6, 3.1, 6.4, 21.7) -> x .Last.value 1/x y <- c(x, 0, x) v <- 2*x + y + 1 ##- Warning message: ##- longer object length ##- is not a multiple of shorter object length in: 2 * x + y sqrt(-17) ##- [1] NaN ##- Warning message: ##- NaNs produced in: sqrt(-17) sqrt(-17+0i) ###-- 2.3 .. regular sequences 1:30 n <- 10 1:n-1 1:(n-1) 30:1 seq(2,10) all(seq(1,30) == seq(to=30, from=1)) seq(-5, 5, by=.2) -> s3 s4 <- seq(length=51, from=-5, by=.2) all.equal(s3,s4) s5 <- rep(x, times=5) temp <- x > 13 z <- c(1:3,NA); ind <- is.na(z) 0/0 Inf - Inf labs <- paste(c("X","Y"), 1:10, sep="") labs x <- c(z,z-2)#-- NOT in texi ; more interesting y <- x[!is.na(x)] (x+1)[(!is.na(x)) & x>0] -> z z x <- c(x, 9:12)# long enough: x[1:10] c("x","y")[rep(c(1,2,2,1), times=4)] y <- x[-(1:5)] y fruit <- c(5, 10, 1, 20) names(fruit) <- c("orange", "banana", "apple", "peach") fruit lunch <- fruit[c("apple","orange")] lunch x x[is.na(x)] <- 0 x y <- -4:9 y[y < 0] <- -y[y < 0] all(y == abs(y)) y ###--------------- z <- 0:9 digits <- as.character(z) digits d <- as.integer(digits) all.equal(z, d) e <- numeric() e[3] <- 17 e alpha <- 10*(1:10) alpha <- alpha[2 * 1:5] alpha winter <- data.frame(temp = c(-1,3,2,-2), cat = rep(c("A","B"), 2)) winter unclass(winter) ###------------ Ordered and unordered factors -------- state <- c("tas", "sa", "qld", "nsw", "nsw", "nt", "wa", "wa", "qld", "vic", "nsw", "vic", "qld", "qld", "sa", "tas", "sa", "nt", "wa", "vic", "qld", "nsw", "nsw", "wa", "sa", "act", "nsw", "vic", "vic", "act") statef <- factor(state) statef levels(statef) incomes <- c(60, 49, 40, 61, 64, 60, 59, 54, 62, 69, 70, 42, 56, 61, 61, 61, 58, 51, 48, 65, 49, 49, 41, 48, 52, 46, 59, 46, 58, 43) incmeans <- tapply(incomes, statef, mean) incmeans stderr <- function(x) sqrt(var(x)/length(x)) incster <- tapply(incomes, statef, stderr) incster ## z <- 1:1500 dim(z) <- c(3,5,100) x <- array(1:20,dim=c(4,5)) # Generate a 4 by 5 array. x i <- array(c(1:3,3:1),dim=c(3,2)) i # @code{i} is a 3 by 2 index array. x[i] # Extract those elements x[i] <- 0 # Replace those elements by zeros. x n <- 60 b <- 5 ; blocks <- rep(1:b, length= n) v <- 6 ; varieties <- gl(v,10) Xb <- matrix(0, n, b) Xv <- matrix(0, n, v) ib <- cbind(1:n, blocks) iv <- cbind(1:n, varieties) Xb[ib] <- 1 Xv[iv] <- 1 X <- cbind(Xb, Xv) N <- crossprod(Xb, Xv) table(blocks,varieties) all(N == table(blocks,varieties)) h <- 1:17 Z <- array(h, dim=c(3,4,2)) Z <- array(0, c(3,4,2)) if(FALSE) D <- 2*A*B + C + 1 a <- 1:9 b <- 10*(1:3) ab <- a %o% b all(ab == outer(a,b,"*")) outer(a,b) x <- 1:10 y <- -2:2 f <- function(x, y) cos(y)/(1 + x^2) z <- outer(x, y, f) d <- outer(0:9, 0:9) fr <- table(outer(d, d, "-")) plot(as.numeric(names(fr)), fr, type="h", xlab="Determinant", ylab="Frequency") ## B <- aperm(A, c(2,1)) A * B A %*% B x %*% A %*% x ev <- eigen(Sm) evals <- eigen(Sm)$values ## SVD ..... absdetM <- prod(svd(M)$d) ans <- lsfit(X, y) Xplus <- qr(X) b <- qr.coef(Xplus, y) fit <- qr.fitted(Xplus, y) res <- qr.resid(Xplus, y) ## X <- cbind(1, X1, X2) vec <- as.vector(X) vec <- c(X) statefr <- table(statef) statefr statefr <- tapply(statef, statef, length) statefr factor(cut(incomes, breaks = 35+10*(0:7))) -> incomef table(incomef,statef) Lst <- list(name="Fred", wife="Mary", no.children=3, child.ages=c(4,7,9)) ## .......... ###--- @chapter Probability distributions ## 2-tailed p-value for t distribution 2*pt(-2.43, df = 13) ## upper 1% point for an F(2, 7) distribution qf(0.99, 2, 7) data(faithful) attach(faithful) summary(eruptions) fivenum(eruptions) stem(eruptions) hist(eruptions) # make the bins smaller, make a plot of density hist(eruptions, seq(1.6, 5.2, 0.2), prob=TRUE) lines(density(eruptions, bw=0.1)) rug(eruptions) # show the actual data points library(stepfun) plot(ecdf(eruptions), do.points=FALSE, verticals=TRUE) long <- eruptions[eruptions > 3] plot(ecdf(long), do.points=FALSE, verticals=TRUE) x <- seq(3, 5.4, 0.01) lines(x, pnorm(x, mean=mean(long), sd=sqrt(var(long))), lty=3) par(pty="s") qqnorm(long); qqline(long) x <- rt(250, df = 5) qqnorm(x); qqline(x) qqplot(qt(ppoints(250), df=5), x, xlab="Q-Q plot for t dsn") qqline(x) library(ctest) shapiro.test(long)