multigmmmanydata {l1kdeconv}

Split the input dataset into several sub list to deconvolution.

Description

Due to the limitation of optimization that too many data would dramatically slow down the speed.

Usage

multigmmmanydata(x, grp_size = 3, lambda_lower = 0.1, lambda_upper = 1 -
  lambda_lower, sigma_lower = 0.01, debug = F)

Arguments

x

a list of numeric vector

grp_size

the normal group size for each group

lambda_lower

the lower bound of \lambda

lambda_upper

the upper bound of \lambda

sigma_lower

the lower bound of \sigma

debug

enable the debug mode to show par and fn

Examples

set.seed(0)
x1=c(rnorm(150, mean=0), rnorm(50, mean=10))
x2=c(rnorm(150, mean=20), rnorm(50, mean=40))
x3=c(rnorm(150, mean=30), rnorm(50, mean=60))
x4=c(rnorm(150, mean=30), rnorm(50, mean=60))
x5=c(rnorm(150, mean=30), rnorm(50, mean=60))
x6=c(rnorm(150, mean=30), rnorm(50, mean=60))
x=list(x1, x2, x3, x4, x5, x6)
multigmmmanydata(x)