fit_poisson_model: Fit a Penalized Spline Poisson Model on a Geometric Network

In geonet: Intensity Estimation on Geometric Networks with Penalized Splines

Fit a Penalized Spline Poisson Model on a Geometric Network

Description

fit_poisson_model is called from intensity_pspline and performs the iterative algorithm to estimate the model parameters and the smoothing parameters rho in the penalized Poisson model.

Usage

fit_poisson_model(data, Z, K, ind, verbose = FALSE, control = list())

Arguments

data	The binned data.
Z	The (sparse) model matrix where the number of columns must correspond to the length of the vector of model coefficients theta.
K	A (sparse) square penalty matrix of with the same dimension as theta.
ind	A list which contains the indices belonging to each smooth term and the linear terms.
verbose	If TRUE, prints information on the process of the fitting algorithm.
control	A list of optional arguments which control the convergence of the fitting algorithm. See "Details".

Details

Smoothing parameters are estimated using the generalized Fellner-Schall method (Wood and Fasiolo, 2017).

Value

Model fit.

Author(s)

Marc Schneble [e-mail]

References

Wood, S. N. and Fasiolo, M. (2017). A generalized Fellner-Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models. Biometrics 73 1071-1081.

geonet documentation built on July 11, 2022, 9:08 a.m.