sim {bliss}  R Documentation 
sim
Description
Simulate a dataset for the Function Linear Regression model.
Usage
sim(param, verbose = FALSE)
Arguments
param 
a list containing:
 beta_shapes
a character vector. The qth item indicates the shape of
the coefficient function associated to the qth functional covariate.
 n
an integer, the sample size.
 p
a vector of integers, the qth component is the number of
times for the qth covariate.
 Q
an integer, the number of functional covariates.
 autocorr_diag
a list of numerical vectors (optional), the qth vector is the
diagonal of the autocorrelation matrix of the qth functional
covariate.
 autocorr_spread
a vector of numerical values (optional) which are related to the
autocorrelation of the functional covariates.
 grids
a list of numerical vectors (optional), the qth vector is the grid
of time points for the qth functional covariate.
 grids_lim
a list of numerical vectors (optional), the qth item is the lower
and upper boundaries of the domain for the qth functional covariate.
 link
a function (optional) to simulate data from the Generalized Functional
Linear Regression model.
 mu
a numerical value (optional), the 'true' intercept of the model.
 r
a nonnegative value (optional), the signal to noise ratio.
 x_shapes
a character vector (optional). The qth item indicates the shape of the
functional covariate observations.

verbose 
write stuff if TRUE.

Value
a list containing:
 Q
an integer, the number of functional covariates.
 y
a numerical vector, the outcome observations.
 x
a list of matrices, the qth matrix contains the observations of the
qth functional covariate at time points given by grids
.
 grids
a list of numerical vectors, the qth vector is the grid of
time points for the qth functional covariate.
 betas
a list of numerical vectors, the qth vector is the 'true' coefficient
function associated to the qth covariate on a grid of time points
given with grids
.
Examples
library(RColorBrewer)
param < list(Q=2,n=25,p=c(50,50),grids_lim=list(c(0,1),c(1,2)))
data < sim(param)
data$y
cols < colorRampPalette(brewer.pal(9,"YlOrRd"))(10)
q=2
matplot(data$grids[[q]],t(data$x[[q]]),type="l",lty=1,col=cols)
plot(data$grids[[q]],data$betas[[q]],type="l")
abline(h=0,lty=2,col="gray")
[Package
bliss version 1.0.2
Index]