DLSSM.plot

Plot smoothed coefficients in the training part and predicted coefficients in validation part, the two parts are divided by vertical dash line.

Implements the dynamic logistic state space model for binary outcome data proposed by Jiang et al. (2021) <doi:10.1111/biom.13593>.
It provides a computationally efficient way to update the prediction whenever new data becomes available.
It allows for both time-varying and time-invariant coefficients, and use cubic smoothing splines to model varying coefficients.
The smoothing parameters are objectively chosen by maximum likelihood. The model is updated using batch data accumulated at pre-specified time intervals.

Jiakun Jiang

DLSSM

Dynamic Logistic State Space Prediction Model

Wei Yang

Wensheng Guo

DLSSM.plot function

<dl><dt>fit</dt>
<dd>fitted object</dd></dl>

Arguments

Jiakun Jiang, Wei Yang and Wensheng Guo

Author

Plot coefficients — DLSSM.plot

<dl>

<dt>fit</dt>
<dd>fitted object</dd>

</dl>

DLSSM.plot: Plot coefficients

Description

Usage

Value

Arguments

Author

Details