R/miscsimulate.R
sim.create_f.Rd
Simulate latent function components for longitudinal data analysis
sim.create_f( X, covariates, relevances, lengthscales, X_affected, dis_fun, bin_kernel, steepness, vm_params, force_zeromean )
X  input data matrix (generated by 

covariates  Integer vector that defines the types of covariates (other than id and age). Different integers correspond to the following covariate types:

relevances  Relative relevance of each component. Must have be a vector
so that 
lengthscales  A vector so that 
X_affected  which individuals are affected by the disease 
dis_fun  A function or a string that defines the disease effect. If
this is a function, that function is used to generate the effect.
If 
bin_kernel  Should the binary kernel be used for categorical
covariates? If this is 
steepness  Steepness of the input warping function. This is only used if the disease component is in the model. 
vm_params  Parameters of the variance mask function. This is only
needed if 
force_zeromean  Should each component (excluding the disease age component) be forced to have a zero mean? 
a data frame FFF where one column corresponds to one additive component