# covTkTl: Finite Sample Covariance between T_k and T_l Values In nnspat: Nearest Neighbor Methods for Spatial Patterns

 covTkTl R Documentation

## Finite Sample Covariance between T_k and T_l Values

### Description

This function computes the exact (i.e., finite sample) covariance between T_k and T_l values which is used in the computation of the exact variance of Cuzick and Edwards T_{comb} test, which is a linear combination of some T_k tests.

The logical argument `nonzero.mat` (default=`TRUE`) is for using the A matrix if `FALSE` or just the matrix of nonzero locations in the A matrix (if `TRUE`) in the computations.

See page 80 of (\insertCitecuzick:1990;textualnnspat) for more details.

### Usage

```covTkTl(dat, n1, k, l, nonzero.mat = TRUE, ...)
```

### Arguments

 `dat` The data set in one or higher dimensions, each row corresponds to a data point. `n1` Number of cases `k` Integers specifying the number of NNs (of subjects i and m in a_{ij}(k) a_{mj}(l)). `l` Integers specifying the number of NNs (of subjects i and m in a_{ij}(k) a_{mj}(l)). `nonzero.mat` A logical argument (default is `TRUE`) to determine whether the A matrix or the matrix of nonzero locations of the A matrix will be used in the computation of N_s and N_t. If `TRUE` the nonzero location matrix is used, otherwise the A matrix itself is used. `...` are for further arguments, such as `method` and `p`, passed to the `dist` function.

### Value

Returns the exact covariance between T_k and T_l values.

Elvan Ceyhan

### References

\insertAllCited

`asycovTkTl`, `covTcomb`, and `Ntkl`

### Examples

```n<-20  #or try sample(1:20,1)
Y<-matrix(runif(3*n),ncol=3)
cls<-sample(0:1,n,replace = TRUE)  #or try cls<-rep(0:1,c(10,10))
n1<-sum(cls==1)

k<-1 #try also 2,3 or sample(1:5,1)
l<-1 #try also 2,3 or sample(1:5,1)
c(k,l)

covTkTl(Y,n1,k,l)
covTkTl(Y,n1,k,l,method="max")
asycovTkTl(Y,n1,k,l)

covTkTl(Y,n1,k,l,nonzero.mat = FALSE)
asycovTkTl(Y,n1,k,l,nonzero.mat = FALSE)

```

nnspat documentation built on Aug. 30, 2022, 9:06 a.m.