Singular Linear Models for Longitudinal Data
Extract Model Coefficients from Singular Linear Model
Laurent Expansion of Inverse of Linear Matrix Function
Confidence Intervals for Model Parameters from Singular Linear Model
Fitter Function for Singular Linear Models
Extract Model Fitted Values from Singular Linear Model
List Covariance Matrices for Every Subject
Model Predictions from Singular Linear Model
Print 'slim' Objects
Extract Model Residuals from Singular Linear Model
Singular linear models for longitudinal data.
Methods for Singular Linear Model Fits
Fit Singular Linear Models
Summarizing Singular Linear Model Fits
Extract Variance-Covariance Matrix from a 'slim' Object
Fits singular linear models to longitudinal data. Singular linear models are useful when the number, or timing, of longitudinal observations may be informative about the observations themselves. They are described in Farewell (2010) <doi:10.1093/biomet/asp068>, and are extensions of the linear increments model <doi:10.1111/j.1467-9876.2007.00590.x> to general longitudinal data.