choose_beta {bliss} R Documentation

## choose_beta

### Description

Compute a coefficient function for the Function Linear Regression model.

### Usage

choose_beta(param)

### Arguments

 param a list containing: grida numerical vector, the time points. pa numerical value, the length of the vector grid. shapea character vector: "smooth", "random_smooth", "simple", "simple_bis", "random_simple", "sinusoid", "flat_sinusoid" and "sharp"

### Details

Several shapes are available.

### Value

A numerical vector which corresponds to the coefficient function at given times points (grid).

### Examples

### smooth
param <- list(p=100,grid=seq(0,1,length=100),shape="smooth")
beta_function <- choose_beta(param)
plot(param$grid,beta_function,type="l") ### random_smooth param <- list(p=100,grid=seq(0,1,length=100),shape="random_smooth") beta_function <- choose_beta(param) plot(param$grid,beta_function,type="l")
### simple
param <- list(p=100,grid=seq(0,1,length=100),shape="simple")
beta_function <- choose_beta(param)
plot(param$grid,beta_function,type="s") ### simple_bis param <- list(p=100,grid=seq(0,1,length=100),shape="simple_bis") beta_function <- choose_beta(param) plot(param$grid,beta_function,type="s")
### random_simple
param <- list(p=100,grid=seq(0,1,length=100),shape="random_simple")
beta_function <- choose_beta(param)
plot(param$grid,beta_function,type="s") ### sinusoid param <- list(p=100,grid=seq(0,1,length=100),shape="sinusoid") beta_function <- choose_beta(param) plot(param$grid,beta_function,type="l")
### flat_sinusoid
param <- list(p=100,grid=seq(0,1,length=100),shape="flat_sinusoid")
beta_function <- choose_beta(param)
plot(param$grid,beta_function,type="l") ### sharp param <- list(p=100,grid=seq(0,1,length=100),shape="sharp") beta_function <- choose_beta(param) plot(param$grid,beta_function,type="l")

[Package bliss version 1.0.5 Index]