Linear Mixed Models with Sparse Matrix Methods and Smoothing
construct object for Automated Differentiation Cholesky decomposition
Construct design matrix for B-Splines
Standard errors for predictions
Coefficients from the mixed model equations of an LMMsolve object.
Helper function for constructing Rinv
Deviance of an LMMsolve object
Give diagnostics for mixed model coefficient matrix C and the cholesky...
Display the sparseness of the mixed model coefficient matrix
Function to get the Effective Dimensions.
Fitted values of an LMMsolve object.
Solve Linear Mixed Models
Fitted LMMsolve Object
Package LMMsolver
Log-likelihood of an LMMsolve object
Function to obtain restricted log-likelihood and the first derivatives...
Family Object for Multinomial Model
Obtain Smooth Trend.
Predict function
Construct equally placed knots
Residuals of an LMMsolve object.
Row-wise kronecker product
Fit P-splines
Summarize Linear Mixed Model fits
Provides tools for fitting linear mixed models using sparse matrix methods and variance component estimation. Applications include spline-based modeling of spatial and temporal trends using penalized splines (Boer, 2023) <doi:10.1177/1471082X231178591>.
Useful links