glm_fit

Runs multiple Fisher scoring steps

Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow'
that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU').
'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers,
variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.

Tomasz Kalinowski

tfprobability

Interface to 'TensorFlow Probability'

Sigrid Keydana

Daniel Falbel

Kevin Kuo

RStudio 

glm_fit function

<dl><dt>x</dt>
<dd>float-like, matrix-shaped Tensor where each row represents a sample's
features.</dd>
<dt>...</dt>
<dd>other arguments passed to specific methods.</dd></dl>

Arguments

Runs multiple Fisher scoring steps — glm_fit

<dl>

<dt>x</dt>
<dd>float-like, matrix-shaped Tensor where each row represents a sample's
features.</dd>


<dt>...</dt>
<dd>other arguments passed to specific methods.</dd>

</dl>

glm_fit: Runs multiple Fisher scoring steps

Description

Usage

Value

Arguments

See Also