{
tol <- 1e-6
T
}
{
#jitter                       # Support for Function gplot.numeric()
exists("jitter")
}
{
#kappa
freevar <- var(freeny.x)
abs(kappa(freevar) - 26.1346295049) < tol
}
{
#kappa.default
abs(kappa.default(freevar) - 26.1346295049) < tol
}
{
#kappa.lm
free.lm <- lm(freeny.y~freeny.x)
abs(kappa.lm(free.lm) - 28548.5081746) < tol
}
{
#kmeans
irismean <- t(apply(iris, c(2, 3), 'mean'))
x <- rbind(iris[,,1], iris[,,2], iris[,,3])
km <- kmeans(x, irismean)
abs(km$withinss[3] - 23.8794631958) < 1e-1
}
{
#kronecker
kn <- kronecker(matrix(1:6,3,2), diag(2))
all(dim(kn)==c(6,4))
}
{
#kruskal.test
holl.y <- c(2.9,3.0,2.5,2.6,3.2,2.8,3.8,2.7,4.0,2.4,2.8,3.4,3.7,2.2,2.0)
holl.grps <- factor(rep(1:3,c(5,5,5)),1:3,c("Normal","OAD","Asb"))
holl.kt <- kruskal.test(holl.y, holl.grps)
abs(holl.kt$statistic - 0.51592128801) < tol
}
{
#ksmooth
kscorn <- ksmooth(corn.yield,ker="parzen",bandwidth=1,n.points=50)
all(names(kscorn)==c("x","y"))
}
{
#l1fit
abs(l1fit(kscorn$x,kscorn$y)$coef[1] + 0.102883979678) < tol
}
{
#labels
length(labels(corn.rain))==38
}
{
#labels.default
length(labels.default(corn.rain))==38
}
{
#labels.lm
labels.lm(free.lm)=="freeny.x"
}
{
#labels.terms
free.terms <- terms(freeny.y~freeny.x)
labels.terms(free.terms)=="freeny.x"
}
{
#labels.model.matrix
# free.mod <- model.matrix(free.terms)
# labels.model.matrix(free.mod)[[2]]["freeny.x1"]=="freeny.x1"
# labels.model.matrix gone on Mar/92 tape.
T
}
{
#labels.tree                  # Tested with the other tree functions
T
}
{
#lag
lag12co2 <- lag(co2, 12)
all(tsp(co2)-tsp(lag12co2)==c(1,1,0))
}
{
#lapply
abs(lapply(guayule,mean)$flats  - 12.5) < tol
}
{
#leaps
free.leaps <- leaps(freeny.x,freeny.y)
abs(free.leaps$Cp[1] - 41.89217376709) < 1e0
}
{
#left.solve                   # Support for Functions lm.hat(), lm.influence()
exists("left.solve")
}
{
#length
length(lynx)==114
}
{
#length<-
mycorn <- corn.rain
length(mycorn)<-10
sum(mycorn) == sum(corn.rain[1:10])
}
{
#levels
is.character(levels(pigment$Batch))
}
{
#levels<-
#levels<-.factor
gun.meth <- gun$Method
levels(gun.meth) <- c("M2","M1")
all.equal.character(levels(gun.meth),rev(levels(gun$Method)))
}
{
#lgamma
abs(lgamma(10)-12.8018274801) < tol
}
{
#library
exists("library")
}
{
#library.dynam
exists("library.dynam")
}
{
#list
is.list(list(one=rep(1:3,34),two=c("dog","cat","rat","pet")))
}
{
#lm
T
}
{
#lm.fit.chol
free.chol <- lm.fit.chol(freeny.x,freeny.y)
abs(free.chol$coefficients["price index"] + 0.847615953099) < tol
}
{
#predict.lm
length(predict.lm(free.chol))==39
}
{
#anova.lm
free.aov <- anova.lm(free.chol)
abs(free.aov$"Sum of Sq" - 0.008031063 ) < tol
}
{
#predict.mlm
length(predict.mlm(free.chol))==39
}
{
#lm.fit.null
free.null <- lm.fit.null(freeny.x,freeny.y)
any(names(free.null)=="residuals")
}
{
#lm.fit.qr                   # Default method
T
}
{
#lm.fit.svd
free.svd <- lm(freeny.y~freeny.x,method="svd")
length(free.svd$coefficients)==5
}
{
#lm.hat
length(lm.hat(free.lm))==39
}
{
#lm.influence
free.infl <- lm.influence(free.lm)
any(names(free.infl)=="hat")
}
{
#lm.kappa
abs(lm.kappa(free.lm) - 28548.5081746) < tol
}
{
#lm.sensitivity
all(round(lm.sensitivity(free.lm)-c(1941332.55587,1260735.32131),4)) < tol
}
{
#lm.wfit
claims.lm <- lm(cost ~ age + type + car.age, claims,
           weights = number, na.action = na.omit)
length(claims.lm$coefficients)==14
}
{
#lms.loc                     # No HELP file , support for lmsreg()
T
}
{
#lmsreg
stacklms <- lmsreg(stack.x, stack.loss)
abs(stacklms$rsquared - 0.983469387755) < tol
}
{
#lo
lo.kyph <- lo(kyphosis$Age,.05)
class(lo.kyph)[1] =="smooth"
}
{
#lo.wam                      # Support for the function gam()
T
}
{
#load.date
is.character(load.date())
}
{
#loess
etha.lo <- loess(NOx ~ C * E, span = 1/2, degree = 2,
           parametric = "C", drop.square = "C",data=ethanol)
etha.lo$errors$family == "gaussian"
}
{
#loess.control
loess.control()$surface == "interpolate"
}
{
#predict.loess
length(predict.loess(etha.lo))==88
}
{
#anova.loess
etha.aov <- anova.loess(etha.lo)
abs(etha.aov$covariance - 0.9773973) < tol
}