Computes the covariance matrix for the cell counts when comparing DNA profiles in a DNA database. For every pair of DNA profiles in a database the number of matching and partial matching loci is recorded. A match is declared if the two DNA profiles coincide for both alleles in a locus and a partial-match is recorded if only one allele is shared between the profiles. With a total of L loci the number of matching loci is 0,...,L and partial number of matches is 0,...,L-m, where m is the number of matching loci. The expression is given by: $$latex$$
dbVariance(probs, theta = 0, n = 1, collapse = FALSE)
| probs | List of vectors with allele probabilities for each locus |
|---|---|
| theta | The coancestery coefficient. If a vector of different theta values are supplied a list of covariance matrices is returned. Note it is faster to give a vector of theta values as argument than calculating each matrix at the time. |
| n | Number of DNA profiles in the database. If n=1 is supplied a list of the components for computing the variance is returned. That is, the variance and two covariances on the right hand side of the equation above. |
| collapse | Logical, default FALSE. If TRUE the covariance matrix is collapsed such that it relates to (2*m+p)-vectors of total number of matching alleles rather than (m,p)-matrix. |
Returns a covariance matrix for the cell counts.
Computes the covariance matrix of the cell counts using a recursion formula. See Tvedebrink et al (2011) for details.
T Tvedebrink, PS Eriksen, J Curran, HS Mogensen, N Morling. 'Analysis of matches and partial-matches in Danish DNA reference profile database'. Forensic Science International: Genetics, 2011.
if (FALSE) { ## Simulate some allele frequencies: freqs <- replicate(10, { g = rgamma(n=10,scale=4,shape=3); g/sum(g)}, simplify=FALSE) ## List of elements needed to compute the covariance matrix. ## Useful option when the covariance needs to be computed for varying ## database sizes but for identical theta-value. comps <- dbVariance(freqs,theta=0,n=1) ## Covariance for a DB with 1000 DNA profiles cov1000 <- dbVariance(freqs,theta=0,n=1000) ## The result is the same as: comps1000 <- choose(1000,2)*comps$V1 + 6*choose(1000,3)*comps$V2 + 6*choose(1000,4)*comps$V3 }