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Nonparametric Regression Methods for Longitudinal Data Analysis: Mixed-Effects Modeling ApproachesBy Hulin Wu and Jin-Ting Zang |
Preface
Contents
Datasets
Matlab Software
Order Book
Matlab Software
1. Introduction
2. Parametric Mixed-Effects Models
3. Nonparametric Regression Smoothers
4. Local Polynomial Methods
- bwselect
- ACmelp.m
- ACmelpfit.m
- BR2step.m
- BR4step.m
- BRmelp.m
- BRmelpfit.m
- BRnlp.m
- glpfit.m
- kerlme1.m
- kerlme.m
- lmefit.m
- lpklme0.m
- lpklme1.m
- lpklme2.m
- lpklme.m
- lplme0.m
- lplme.m
- lplmeRE.m
5. Regression Spline Methods
- ACmers.m
- ACnrsfit.m
- BRmers.m
- BRnrsfit.m
- fdadat.m
- lmefit.m
- nrsfit.m
- nrsfits.m
- rgsplQ.m
- RSbwc.m
- rsplbas.m
- rsplme0.m
- rsplme.m
- rsplQ.m
6. Smoothing Splines Methods
7. Penalized Spline Methods
- ACmeps0.m
- ACmeps.m
- ACmepsK.m
- ACnps.m
- ACnpsK.m
- BRmeps.m
- BRnps.m
- fdadat.m
- findh.m
- npsfit.m
- nrsfit.m
- ps2rs.m
- pslme0.m
- pslme.m
- psplme0.m
- psplme.m
8. Semiparametric Models
9. Time-Varying Coefficient Models