Description Usage Arguments Details Value Author(s) See Also Examples
Notably distant targets are those with relatively large distances from the closest reference observation. A suitable threshold is used to detect large distances.
1  notablyDistant(object,kth=1,threshold=NULL,p=0.01,method="distribution")

object 
an object of class 
kth 
the kth neighbor is used. 
threshold 
the thereshold distance that identifies notably large distances between observations. 
p 

method 
the method used to compute the threshold, see details. 
When threshold
is NULL, the function computes one using one of
two methods. When method
is "distribution", assumption is made that
distances follow the lognormal distribution, unless the method used
to find neighbors is randomForest
, in which case the distances
are assumed to follow the beta distribution. A specified p
value
is used to compute the threshold
, which is the point in the distribution
where a fraction, p
, of the neighbors are larger than the threshold
.
When method
is "quantile", the function uses the quantile
function with probs=1p
.
List of two data frames that contain 1) the references that are notably distant from other references, 2) the targets that are notably distant from the references, 3) the threshold used, and 4) the method used.
Nicholas L. Crookston [email protected]
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  data(iris)
set.seed(12345)
# form some test data
refs=sample(rownames(iris),50)
x < iris[,1:3] # Sepal.Length Sepal.Width Petal.Length
y < iris[refs,4:5] # Petal.Width Species
# build an msn run, first build dummy variables for species.
sp1 < as.integer(iris$Species=="setosa")
sp2 < as.integer(iris$Species=="versicolor")
y2 < data.frame(cbind(iris[,4],sp1,sp2),row.names=rownames(iris))
y2 < y2[refs,]
names(y2) < c("Petal.Width","Sp1","Sp2")
msn < yai(x=x,y=y2,method="msn")
notablyDistant(msn)

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