Barebone function to compute starting points for B, M and S2 when fitting a PLN. Mostly intended for internal use.
Usage
compute_PLN_starting_point(Y, X, O, w, method = c("LM", "GLM"))Arguments
- Y
Response count matrix
- X
Covariate matrix. Note that initialization will fail if the model matrix is singular.
- O
Offset matrix (in log-scale)
- w
Weight vector (defaults to 1)
- method
character: strategy used to initialize B. Either
"LM"(default, fast weighted log-linear regression) or"GLM"(p independent Poisson GLMs, more accurate for complex or unbalanced designs but slower).
Value
a named list of starting values for model parameter B and variational parameters M and S2 used in the iterative optimization algorithm of PLN()
Details
B: estimated by weighted LM (
method = "LM", default) or p independent Poisson GLMs (method = "GLM"). The GLM option gives better B estimates for factorial or unbalanced designs at the cost of p IRLS fits.M: initialized to
log((1 + Y) / exp(O))(M_full in the X*B + M_res parameterization).S: initialized element-wise to
1 / sqrt(2 + Y), the approximate VE-step optimum at Omega = I. This adapts automatically to count levels: high S for zero counts (high uncertainty), low S for large counts.
Examples
if (FALSE) { # \dontrun{
data(barents)
Y <- barents$Abundance
X <- model.matrix(Abundance ~ Latitude + Longitude + Depth + Temperature, data = barents)
O <- log(barents$Offset)
w <- rep(1, nrow(Y))
compute_PLN_starting_point(Y, X, O, w)
compute_PLN_starting_point(Y, X, O, w, method = "GLM")
} # }