probUxUy {dcifer}

Likelihood for U_x, U_y

Description

Calculates log-likelihood for a pair of samples at a single locus.

Usage

probUxUy(
  Ux,
  Uy,
  nx,
  ny,
  probs,
  M,
  logj,
  factj,
  equalr = FALSE,
  mnewton = TRUE,
  reval = NULL,
  logr = NULL,
  neval = NULL
)

Arguments

Ux, Uy

sets of unique alleles for two samples at a given locus. Vectors of indices corresponding to ordered probabilities in probs.

nx, ny

complexity of infection for two samples. Vectors of length 1.

probs

a vector of population allele frequencies (on a log scale) at a given locus. It is not checked if frequencies on a regular scale sum to 1.

M

the number of related pairs of strains.

logj, factj

numeric vectors containing precalculated logarithms and factorials.

equalr

a logical value. If TRUE, the same level of relatedness is assumed for M pairs of strains (r₁ = ... = r_M).

mnewton

a logical value. If TRUE, the coefficients for using Newton's method will be calculated.

reval

a matrix representing a grid of (r₁, ..., r_M) combinations, over which the likelihood will be calculated. Each column is a single combination.

logr

a list of length 5 as returned by logReval.

neval

the number of relatedness values/combinations to evaluate over.

Value

• If mnewton = TRUE, a vector of length 2 containing coefficients for fast likelihood calculation;

• If mnewton = FALSE, a vector of length neval containing log-likelihoods for a range of parameter values.

Examples

Ux <- c(1, 3, 7)                       # detected alleles at locus t
Uy <- c(2, 7)
coi <- c(5, 6)
aft <- runif(7)                        # allele frequencies for locus t
aft <- log(aft/sum(aft))

logj  <- log(1:max(coi))
factj <- lgamma(0:max(coi) + 1)

# M = 2, equalr = FALSE
M <- 2
reval <- generateReval(M, nr = 1e2)
logr  <- logReval(reval, M = M)
llikt <- probUxUy(Ux, Uy, coi[1], coi[2], aft, M, logj, factj,
                  equalr = FALSE, logr = logr, neval = ncol(reval))
length(llikt)

# M = 2, equalr = TRUE
reval <- matrix(seq(0, 1, 0.001), 1)
logr  <- logReval(reval, M = M, equalr = TRUE)
llikt <- probUxUy(Ux, Uy, coi[1], coi[2], aft, M, logj, factj,
                  equalr = TRUE, logr = logr, neval = ncol(reval))

# M = 1, mnewton = FALSE
M <- 1
reval <- matrix(seq(0, 1, 0.001), 1)
logr  <- logReval(reval, M = M)
llikt <- probUxUy(Ux, Uy, coi[1], coi[2], aft, M, logj, factj,
                  mnewton = FALSE, reval = reval, logr = logr,
                  neval = ncol(reval))

# M = 1, mnewton = TRUE
probUxUy(Ux, Uy, coi[1], coi[2], aft, M, logj, factj, mnewton = TRUE)