vem_grad: VEM algorithm for univariate data, for bivariate data and for...

Description Usage Arguments Examples

View source: R/CAMAN.R

Description

This function

Usage

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vem_grad(obs1, obs2, type, data, var1, var2, 
         lambda1, lambda2, p, startk, 
         numiter=5000, acc=1.e-7)

Arguments

obs1

the first column of the observations


obs2

the second column of the observations


type

kind of data


data

an optional data frame


lambda1

Means of the first column of the observations


lambda2

Means of the second column of the observations


p

Mixing weight


var1

Variance of the first column of the observations(only for meta-analysis)


var2

Variance of the second column of the observations (only for meta-analysis)


startk

starting/maximal number of components. This number will be used to compute the grid in the VEM. Default is 20.)


numiter

parameter to control the maximal number of iterations in the VEM and EM loops. Default is 5000.


acc

convergence criterion. Default is 1.e-7


Examples

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## Not run: 
#1.	VEM-algorithm  for bivariate normally distributed data 
#Examples
data(rs12363681)
vem_grad(obs1=x,obs2=y,type="bi", data=rs12363681,startk=20)
#2.VEM for metadata
data(CT)
vem_grad(obs1=logitTPR, obs2= logitTNR, 
         var1= varlogitTPR, var2= varlogitTNR,
         type="meta", data=CT, startk=20)

## End(Not run)

CAMAN documentation built on May 1, 2019, 9:21 p.m.

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