init1.1.jk.j {poisson.glm.mix} | R Documentation |
1st step of Initialization 1 for the \beta_{jk}
(m=1
) or \beta_{j}
(m=2
) parameterization.
Description
This function is the first step of the two-step small initialization procedure (Initialization 1), used for the parameterizations m=1
(\beta_{jk}
) or m=2
(\beta_{j}
). For each condition j=1,\ldots,J
, a small EM is run in order to find some good starting values for the K
-component mixtures: \sum_{k=1}^{K}p_j\prod_{\ell=1}^{L_j}f(y_{ij\ell})
, independently for each j=1,\ldots,J
. These values are used in order to initialize the second step (init1.2.jk.j
) of the small EM algorithm for fitting the overall mixture \sum_{k=1}^{K}\pi_j\prod_{j=1}^{J}\prod_{\ell=1}^{L_j}f(y_{ij\ell})
.
Usage
init1.1.jk.j(reference, response, L, K, t1, model, m1,mnr)
Arguments
reference |
a numeric array of dimension |
response |
a numeric array of count data with dimension |
L |
numeric vector of positive integers containing the partition of the |
K |
positive integer denoting the number of mixture components. |
t1 |
positive integer denoting the number of different runs. |
model |
binary variable denoting the parameterization of the model: 1 for |
m1 |
positive integer denoting the number of iterations for each run. |
mnr |
positive integer denoting the maximum number of Newton-Raphson iterations. |
Value
alpha |
numeric array of dimension |
beta |
numeric array of dimension |
psim |
numeric vector of length |
ll |
numeric, the value of the loglikelihood, computed according to the |
Author(s)
Panagiotis Papastamoulis
See Also
init1.2.jk.j
, bjkmodel
, bjmodel
Examples
############################################################
#1. Example with beta_jk (m=1) model #
############################################################
## load a simulated dataset according to the b_jk model
## number of observations: 500
## design: L=(3,2,1)
data("simulated_data_15_components_bjk")
x <- sim.data[,1]
x <- array(x,dim=c(length(x),1))
y <- sim.data[,-1]
## initialize the component specific parameters
## for a 2 component mixture
start1 <- init1.1.jk.j(reference=x, response=y, L=c(3,2,1),
K=2, t1=3, model=1, m1=5,mnr = 5)
summary(start1)
############################################################
#2. Example with beta_j (m=2) model #
############################################################
start1 <- init1.1.jk.j(reference=x, response=y, L=c(3,2,1),
K=2, t1=3, model=2, m1=5,mnr = 5)
summary(start1)