MangroveTree {Mangrove}

The MangroveTree class

Description

Functions to create, populate, summarise and utilise MangroveTree objects.

Usage

initialiseTree()

# Member functions: 
# tree$addPed(ped,ORs)
# tree$getPrevs(ORs = NULL,K = NULL,overwrite=FALSE,iter=1000)

## S3 method for class 'MangroveTree'
print(x,...)
## S3 method for class 'MangroveTree'
summary(object,...)
## S3 method for class 'MangroveTree'
plot(x,...)

Arguments

tree

An object of class MangroveTree

x

An object of class MangroveTree

object

An object of class MangroveTree

ped

An object of class \codeMangrovePed

ORs

An object of class MangroveORs

K

The prevalence of the disease (between 0 and 1, or NULL if not known)

overwrite

Logical. If set to FALSE, and sampling has already been performed, then existing samples will be used. If TRUE, sampling is performed again.

iter

Number of samples to draw from the posterior distribution of number of affecteds.

...

Arguments to be passed on to other methods.

Details

The MangroveTree class is used for holding family trees, and for performing risk prediction on them. The initialiseTree function creates an empty tree, and the tree$addPed populates it from genetic data. You can then sample from the posterior distribution of number of affecteds using the tree$getPrevs function.

The print method writes a text version of the tree to screen, and the summary method writes some basic information about what the tree contains, along with what calculations have and have not been performed on it. The plot method is not implemented, and throws an error message.

To see an example of the use of this class, use vignette("Mangrove").

Value

For initialiseTree, an empty object of class MangroveTree. For the tree$getPrevs class function, an object of class MangroveSample.

For all other functions, nothing is returned.

See Also

MangrovePed, MangroveORs, MangroveSample

Examples

data(famped)
data(exampleORs)

tree <- initialiseTree()
tree$addPed(famped,exampleORs)

print(tree)
summary(tree)

sam <- tree$getPrevs(exampleORs,K=0.02)
summary(sam)