R: Set tables for auxiliary variables 'Q'

setCPT.Q {DNAmixturesLite}

R Documentation

Set tables for auxiliary variables `Q`

Description

Function for setting the tables on all nodes Q_r_a for mixture r in the network corresponding to one marker, using peak heights and a set of parameters.

IMPORTANT: This is the DNAmixturesLite package, which is intended as a service to enable users to try DNAmixtures without purchasing a commercial licence for Hugin. When at all possible, we strongly recommend the use of DNAmixtures rather than this lite-version. See https://dnamixtures.r-forge.r-project.org/ for details on both packages.

While the lite-version seeks to provide the full functionality of DNAmixtures, note that computations are much less efficient and that there are some differences in available functionality. Be aware that the present documentation is copied from DNAmixtures and thus may not accurately describe the implementation of this lite-version.

Usage

setCPT.Q(
  domain,
  rho,
  xi,
  eta,
  phi,
  heights,
  n.unknown,
  n_K,
  Q,
  gets_stutter,
  can_stutter,
  stutter.from
)

Arguments

`domain`	A `hugin.domain` modelling one marker
`rho`	rho
`xi`	xi
`eta`	eta
`phi`	phi ordered as `phi[c(U,K)]` where `U` and `K` are the names of unknown and known contributors.
`heights`	Observed peak heights
`n.unknown`	Number of unknown contributors
`n_K`	Allelecounts for known contributors
`Q`	Names for binary nodes
`gets_stutter`	Does the allele receive stutter?
`can_stutter`	Can the allele stutter?
`stutter.from`	From which allele does the stutter come?

Details

The function sets conditional probabilities for auxiliary variables Q_r_a, which are used for finding probabilities of observing a smaller or larger peak than the one observed for the DNA mixture. The conditional probability tables are defined using the gamma c.d.f. as

P(\texttt{Q[a]} = \texttt{TRUE} | n_{ia}, n_{i,a+1}, i = 1,\ldots, k) = G(\texttt{heights[a]}).

Value

Scaling factors to be set as evidence when conditioning on the peak heights

Author(s)

Therese Graversen

Set tables for auxiliary variables Q