Module poisson 

Poisson-likelihood fitting of counts.

Minimizes half the Poisson deviance

D(θ) = Σᵢ [μᵢ(θ) − yᵢ + yᵢ ln(yᵢ / μᵢ(θ))]

within box bounds, by projected Levenberg–Marquardt steps in the Fisher metric, for models with an analytical Jacobian.

Scope note. The production pipeline does not apply this single-arm objective to normalized transmission. Raw open/sample counts use the joint-Poisson conditional-binomial-deviance solver in crate::joint_poisson. This module remains available to the evaluate_jacobian_and_fisher Fisher-information helper (via CountsModel, CountsBackgroundScaleModel and TransmissionKLBackgroundModel, all three of which that helper still constructs) and to spatial-regularization research drivers; it is not a public transmission fitting route.

Structs

CountsBackgroundScaleModel

Fixed-flux counts model with optional α₁ / α₂ nuisance scaling of signal and detector background.

CountsModel

Fixed-flux counts-domain forward model: Y_model = flux × T_model(θ) + background.

PoissonConfig

Configuration for the Poisson solvers.

PoissonResult

Result of poisson_fit.

TransmissionKLBackgroundModel

KL-compatible background model for transmission data.

Functions

poisson_fit

Fit params to the counts y_obs by minimizing half the Poisson deviance within the parameter bounds.