13 citations · 14 across the 3 of their papers we have counts for
3 papers
Structured Secant Methods to Select Smoothing Parameters for General Smooth Models
Joshua Krause, Jelmer P. Borst, Jacolien van Rij
General smooth models replace parameters of a regular likelihood with additive models. The models can include parametric terms, Gaussian random effects, and smooth functions of cov…
The Mixed-Sparse-Smooth-Model Toolbox (MSSM): Efficient Estimation and Selection of Large Multi-Level Statistical Models
Joshua Krause, Jelmer P. Borst, Jacolien van Rij
Additive smooth models, such as Generalized additive models (GAMs) of location, scale, and shape (GAMLSS), are a popular choice for modeling experimental data. However, software av…
Autocorrelated errors in experimental data in the language sciences: Some solutions offered by Generalized Additive Mixed Models
R. Harald Baayen, Jacolien van Rij, Cecile de Cat +1
A problem that tends to be ignored in the statistical analysis of experimental data in the language sciences is that responses often constitute time series, which raises the proble…