The AA-Aa-aa Blood Group System
Estimates the parameter of the AA-Aa-aa blood group system, with or without Hardy Weinberg equilibrium.
AA.Aa.aa(linkp = "logitlink", linkf = "logitlink", inbreeding = FALSE,
ipA = NULL, ifp = NULL, zero = NULL)linkp, linkf |
Link functions applied to |
ipA, ifp |
Optional initial values for |
inbreeding |
Logical. Is there inbreeding? |
zero |
See |
This one or two parameter model involves a probability called pA.
The probability of getting a count in the first column of the
input (an AA) is pA*pA.
When inbreeding = TRUE, an additional parameter f is used.
If inbreeding = FALSE then f = 0 and Hardy-Weinberg
Equilibrium (HWE) is assumed.
The EIM is used if inbreeding = FALSE.
An object of class "vglmff" (see vglmff-class).
The object is used by modelling functions such as vglm
and vgam.
Setting inbreeding = FALSE makes estimation difficult
with non-intercept-only models.
Currently, this code seems to work with intercept-only models.
The input can be a 3-column matrix of counts, where the columns
are AA, Ab and aa
(in order).
Alternatively, the input can be a 3-column matrix of
proportions (so each row adds to 1) and the weights
argument is used to specify the total number of counts for each row.
T. W. Yee
Weir, B. S. (1996). Genetic Data Analysis II: Methods for Discrete Population Genetic Data, Sunderland, MA: Sinauer Associates, Inc.
AB.Ab.aB.ab,
ABO,
A1A2A3,
MNSs.
y <- cbind(53, 95, 38) fit1 <- vglm(y ~ 1, AA.Aa.aa, trace = TRUE) fit2 <- vglm(y ~ 1, AA.Aa.aa(inbreeding = TRUE), trace = TRUE) rbind(y, sum(y) * fitted(fit1)) Coef(fit1) # Estimated pA Coef(fit2) # Estimated pA and f summary(fit1)
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