| generate_glmpca_data_pois {fastglmpca} | R Documentation |
Generate Data from a GLMCPA Model
Description
Generate data from a GLMPCA model with a specified rank.
Usage
generate_glmpca_data_pois(n, p, K, link = c("log", "log1p"))
Arguments
n |
Number of rows (genes). |
p |
Number of columns (cells). |
K |
Rank of the underlying mean structure |
link |
Character vector describing the link between the product of the loading and factors and the mean of the data. |
Details
This function assumes that each column of the data is generated from a multinomial distribution. Let
Y_j
denote column j of the generated data matrix. First, we set
sum(Y_j)
equal to a value generated from a
Uniform(50, 5000)
distribution. Then, we generate
L
and
F
from mixture distributions, and calculate
H = exp(L'F)
. Then, we generate the individual elements of
Y_j
from a multinomial model where the probability for each individual element is just
H_j
normalized.
Value
list with the following components
LL - loadings of underlying mean structure. A K x n matrix
FF - factors of underlying mean structure. A K x p matrix
Y - n x p matrix of generated data.
Examples
set.seed(1)
sim_data <- generate_glmpca_data_pois(1000, 500, 1)