info_negbin: Compute Negative Binomial Observed Information Matrix
In lgspline: Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation
View source: R/negbin_helpers.R
info_negbin R Documentation
Compute Negative Binomial Observed Information Matrix
Description
Negative Hessian of the NB2 log-likelihood with respect to
\boldsymbol{\beta} under the log link.
Usage
info_negbin(X, y, mu, theta, weights = 1)
Arguments
X
Design matrix (N x p).
mu
Mean vector.
theta
Shape parameter.
weights
Observation weights (default 1).
Details
The expected information under log link is
\mathbf{I} = \mathbf{X}^{\top}\mathbf{W}\mathbf{X}
where W_{ii} = w_i \mu_i \theta / (\theta + \mu_i).
This is the IRLS weight for NB2 with log link.
Value
Symmetric p x p observed information matrix.
lgspline documentation built on May 8, 2026, 5:07 p.m.
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View source: R/negbin_helpers.R
| info_negbin | R Documentation |
Compute Negative Binomial Observed Information Matrix
Description
Negative Hessian of the NB2 log-likelihood with respect to
\boldsymbol{\beta} under the log link.
Usage
info_negbin(X, y, mu, theta, weights = 1)
Arguments
X |
Design matrix (N x p). |
mu |
Mean vector. |
theta |
Shape parameter. |
weights |
Observation weights (default 1). |
Details
The expected information under log link is
\mathbf{I} = \mathbf{X}^{\top}\mathbf{W}\mathbf{X}
where W_{ii} = w_i \mu_i \theta / (\theta + \mu_i).
This is the IRLS weight for NB2 with log link.
Value
Symmetric p x p observed information matrix.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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