Description Usage Arguments Details Value Author(s)
A simplified version of glm
that does only parameter estimation
1 |
predictors |
The columns of the standard design matrix to include in the model. For example, "c1", "c2" for main effects, and "c12" for interactions. |
data |
A design matrix with cell counts included |
normalized |
Logical: If TRUE, include a normalization step after coefficient estimation, which resets the value of the intercept so that the sum of predicted values is exactly 1 |
precision |
Controls the precision of the coefficient estimates. A higher number is less precise. 1 corresponds to machine epsilon. |
Maximize the Poisson likelihood using BFGS in optim()
.
The vector of estimated log-linear coefficients. The first
coefficient is the intercept, and the remaining ones correspond to the
predictors
argument, in that order
Zach Kurtz
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.