# multiRDPG_test: Performs test based on Multiple Random Dot Product Graph In multiRDPG: Multiple Random Dot Product Graphs

## Description

`multiRDPG_test` calculates the likelihood ratio test for whether a set of graphs comes from the same disribution.

## Usage

 `1` ```multiRDPG_test(A, d, maxiter = 100, tol = 1e-06, B = 1000) ```

## Arguments

 `A` List of symmetric A matrices `d` Dimension of the latent space `maxiter` Maximum number of iterations in the fit of multiRDPG. Default is 100. `tol` Tolerance for the step in the objective function in multiRDPG. Default is 1e-6. `B` Number of permutation iterations. Default is 1000.

## Value

Returns a list of the following elements:

 `pvalue` Estimated p-values `Tval` Value of the test statistic `Tstar` Vector of the test statistic for each permutation iteration `nullmodel` Model fit under the null `altmodel` Modelfit under the alternative

## Author(s)

Agnes Martine Nielsen ([email protected])

`multiRDPG`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```#simulate data U <- matrix(0, nrow=20, ncol=3) U[,1] <- 1/sqrt(20) U[,2] <- rep(c(1,-1), 10)/sqrt(20) U[,3] <- rep(c(1,1,-1,-1), 5)/sqrt(20) L<-list(diag(c(11,6,2)),diag(c(15,4,1))) A <- list() for(i in 1:2){ P <- U%*%L[[i]]%*%t(U) A[[i]] <-apply(P,c(1,2),function(x){rbinom(1,1,x)}) A[[i]][lower.tri(A[[i]])]<-t(A[[i]])[lower.tri(A[[i]])] } #perform test multiRDPG_test(A,3,B=100) ```