smooth.construct.fdl.smooth.spec

Originally proposed in Obermeier et al., 2015, Flexible Distributed Lags for Modelling Earthquake Data,
Journal of the Royal Statistical Society: Series C (Applied Statistics),
10.1111/rssc.12077.
Here extended in order to penalize lead times in addition to lag times.
Ideally the lag-lead window would then be selected in a data-driven fashion.
Treat as experimental.

internal

The Piece-wise exponential (Additive Mixed) Model
(PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a
powerful model class for the analysis of survival (or time-to-event) data,
based on Generalized Additive (Mixed) Models (GA(M)Ms).
It offers intuitive specification and robust estimation of complex survival
models with stratified baseline hazards, random effects, time-varying effects,
time-dependent covariates and cumulative effects (Bender and others (2019)),
as well as support for left-truncated data as well as competing risks,
recurrent events and multi-state settings.
pammtools provides tidy workflow for survival analysis with PAMMs,
including data simulation, transformation and other functions for data
preprocessing and model post-processing as well as visualization.

Andreas Bender

pammtools

Piece-Wise Exponential Additive Mixed Modeling Tools for
Survival Analysis

Fabian Scheipl

Johannes Piller

Philipp Kopper

Lukas Burk

smooth.construct.fdl.smooth.spec function

<dl><dt>object</dt>
<dd>An object handled by mgcv</dd>
<dt>data</dt>
<dd>The data set</dd>
<dt>knots</dt>
<dd>A vector of knots</dd></dl>

Arguments

New basis for penalized lag selection — smooth.construct.fdl.smooth.spec

<dl>

<dt>object</dt>
<dd>An object handled by mgcv</dd>


<dt>data</dt>
<dd>The data set</dd>


<dt>knots</dt>
<dd>A vector of knots</dd>

</dl>

smooth.construct.fdl.smooth.spec: New basis for penalized lag selection

Description

Usage

Arguments