funsW345values | R Documentation |
W_k
values for Tango's T
test statisticThree functions: W3val
, W4val
and W5val
, each of which is needed to compute E[T^3]
(i.e., for the skewness of T
)
where T=T(\theta)
which is defined in Equation (2) of \insertCitetango:2007;textualnnspat as follows:
Let (z_1,\ldots,z_n )
, n = n_0 + n_1
, denote the locations of the points in the combined sample
when the indices have been randomly permuted so that the z_i
contain no information about group membership.
T(\theta)=\sum_{i=1}^{n}\sum_{j=1}^{n}\delta_i \delta_j a_{ij}(\theta)=
\boldsymbol \delta^t \boldsymbol A(\theta)) \boldsymbol \delta
where \delta_i=1
if z_i
is a case,
and 0 if z_i
is a control, \boldsymbol A(\theta) = (a_{ij} (\theta))
could be any matrix of a measure of
the closeness between two points i
and j
with a_{ii} = 0
for all i = 1,\ldots,n
, and \boldsymbol \theta =
(\theta_1,\ldots,\theta_p)^t
denotes the unknown parameter vector related to cluster size and
\boldsymbol \delta = (\delta_1,\ldots,\delta_n)^t
.
Here the number of cases are denoted as n_1
and number of controls as n_0
to match the case-control class
labeling, which is just the reverse of the labeling in \insertCitetango:2007;textualnnspat.
If \theta=k
in the nearest neighbors model with a_{ij}(k) = 1
if z_j
is among the k
NNs of z_i
and 0
otherwise, then the test statistic T(\theta) = T_k
is the Cuzick and Edwards k
NN test statistic, T_k
\insertCitecuzick:1990;textualnnspat, see also ceTk
.
W_k
values are used for Tango's correction to Cuzick and Edwards k
NN test statistic, T_k
and
W_k
here corresponds to W_{k-1}
in \insertCitetango:2007;textualnnspat
(defined for consistency with p_k
's and alpha_r
having r
distinct elements).
The argument of the function is the A_{ij}
matrix, a
, which is the output of the function aij.mat
.
However, inside the function we symmetrize the matrix a
as b <- (a+a^t)/2
, to facilitate the formulation.
W3val(a)
W4val(a)
W5val(a)
a |
|
Each function Wkval
returns the W_k
value for k=3,4,5
.
Elvan Ceyhan
ceTk
, EV.Tk
, varTk
, Xsq.ceTk
n<-20 #or try sample(1:20,1)
Y<-matrix(runif(3*n),ncol=3)
k<-sample(1:5,1) # try also 3, 5, sample(1:5,1)
k
a<-aij.mat(Y,k)
W3val(a)
W4val(a)
W5val(a)
a<-aij.mat(Y,k,method="max")
W3val(a)
W4val(a)
W5val(a)
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