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> options(width = 70, prompt = "R> ", continue = "+ ")
> library("Formula")
> set.seed(1090)
> dat <- as.data.frame(matrix(round(runif(21), digits = 2),
+ ncol = 7))
> colnames(dat) <- c("y1", "y2", "y3", "x1", "x2", "x3",
+ "x4")
> for (i in c(2, 6:7)) dat[[i]] <- factor(dat[[i]] <
+ 0.5, labels = c("a", "b"))
> dat$y2[1] <- NA
> dat
y1 y2 y3 x1 x2 x3 x4
1 0.82 <NA> 0.27 0.09 0.22 a b
2 0.70 a 0.17 0.26 0.46 b b
3 0.65 b 0.28 0.03 0.37 a a
> F1 <- Formula(log(y1) ~ x1 + x2 | I(x1^2))
> length(F1)
[1] 1 2
> mf1 <- model.frame(F1, data = dat)
> mf1
log(y1) x1 x2 I(x1^2)
1 -0.1984509 0.09 0.22 0.0081
2 -0.3566749 0.26 0.46 0.0676
3 -0.4307829 0.03 0.37 9e-04
> model.response(mf1)
1 2 3
-0.1984509 -0.3566749 -0.4307829
> model.matrix(F1, data = mf1, rhs = 1)
(Intercept) x1 x2
1 1 0.09 0.22
2 1 0.26 0.46
3 1 0.03 0.37
attr(,"assign")
[1] 0 1 2
> model.matrix(F1, data = mf1, rhs = 2)
(Intercept) I(x1^2)
1 1 0.0081
2 1 0.0676
3 1 0.0009
attr(,"assign")
[1] 0 1
> F2 <- Formula(y1 + y2 ~ x3)
> length(F2)
[1] 1 1
> mf2 <- model.frame(F2, data = dat)
> mf2
y1 y2 x3
2 0.70 a b
3 0.65 b a
> model.response(mf2)
NULL
> model.part(F2, data = mf2, lhs = 1)
y1 y2
2 0.70 a
3 0.65 b
> model.part(F1, data = mf1, lhs = 1, drop = TRUE)
1 2 3
-0.1984509 -0.3566749 -0.4307829
> F3 <- Formula(y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 +
+ log(x1) | x3/x4)
> F3
y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 + log(x1) | x3/x4
> length(F3)
[1] 2 3
> attr(F3, "lhs")
[[1]]
y1 + y2
[[2]]
log(y3)
> formula(F3)
y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 + log(x1) | x3/x4
> formula(F3, lhs = 2, rhs = -2)
log(y3) ~ x1 + I(x2^2) | x3/x4
> formula(F3, lhs = c(TRUE, FALSE), rhs = 0)
y1 + y2 ~ 0
> terms(F3)
~y1 + y2 + log(y3) + (x1 + I(x2^2)) + (0 + log(x1)) + x3/x4
attr(,"variables")
list(y1, y2, log(y3), x1, I(x2^2), log(x1), x3, x4)
attr(,"factors")
y1 y2 log(y3) x1 I(x2^2) log(x1) x3 x3:x4
y1 1 0 0 0 0 0 0 0
y2 0 1 0 0 0 0 0 0
log(y3) 0 0 1 0 0 0 0 0
x1 0 0 0 1 0 0 0 0
I(x2^2) 0 0 0 0 1 0 0 0
log(x1) 0 0 0 0 0 1 0 0
x3 0 0 0 0 0 0 1 2
x4 0 0 0 0 0 0 0 1
attr(,"term.labels")
[1] "y1" "y2" "log(y3)" "x1" "I(x2^2)" "log(x1)"
[7] "x3" "x3:x4"
attr(,"order")
[1] 1 1 1 1 1 1 1 2
attr(,"intercept")
[1] 0
attr(,"response")
[1] 0
attr(,".Environment")
<environment: R_GlobalEnv>
> formula(terms(F3))
~y1 + y2 + log(y3) + (x1 + I(x2^2)) + (0 + log(x1)) + x3/x4
> formula(terms(F3, lhs = 2, rhs = -2))
log(y3) ~ x1 + I(x2^2) + x3/x4
> formula(terms(F3, lhs = c(TRUE, FALSE), rhs = 0))
~y1 + y2
> mf3 <- model.frame(F3, data = dat, subset = y1 < 0.75,
+ weights = x1)
> mf3
y1 y2 log(y3) x1 I(x2^2) log(x1) x3 x4 (weights)
2 0.70 a -1.771957 0.26 0.2116 -1.347074 b b 0.26
3 0.65 b -1.272966 0.03 0.1369 -3.506558 a a 0.03
> model.matrix(F3, data = mf3, rhs = 2)
log(x1)
2 -1.347074
3 -3.506558
attr(,"assign")
[1] 1
> model.part(F3, data = mf3, lhs = 1)
y1 y2
2 0.70 a
3 0.65 b
> model.part(F3, data = mf3, lhs = 2)
log(y3)
2 -1.771957
3 -1.272966
> model.weights(mf3)
[1] 0.26 0.03
> update(F1, . ~ . - x1 | . + x1)
log(y1) ~ x2 | I(x1^2) + x1
> update(F1, . + y2 | y3 ~ .)
log(y1) + y2 | y3 ~ x1 + x2 | I(x1^2)
> as.Formula(y1 ~ x1, y2 ~ x2, ~x3)
y1 | y2 ~ x1 | x2 | x3
> ivcoef <- function(formula, data, subset, na.action,
+ ...) {
+ mf <- match.call(expand.dots = FALSE)
+ m <- match(c("formula", "data", .... [TRUNCATED]
> ivcoef(log(y1) ~ x1 | x2, data = dat)
(Intercept) x1
-0.169027 -1.260073
*** Run successfully completed ***
|
