compute_PLN_starting_point: Helper function for PLN initialization.

In PLNmodels: Poisson Lognormal Models

Helper function for PLN initialization.

Description

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).

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.

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()

Examples

## Not run: 
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")

## End(Not run)

PLNmodels documentation built on July 27, 2026, 5:09 p.m.