generateBatchDataMVT {batchmix}

Generate batch data from a multivariate t distribution

Description

Generate data from K multivariate t distributions with additional noise from batches. Assumes independence across columns. In each column the parameters are randomly permuted for both the groups and batches.

Usage

generateBatchDataMVT(
  N,
  P,
  group_means,
  group_std_devs,
  batch_shift,
  batch_scale,
  group_weights,
  batch_weights,
  dfs,
  frac_known = 0.2
)

Arguments

N

The number of items (rows) to generate.

P

The number of columns in the generated dataset.

group_means

A vector of the group means for a column.

group_std_devs

A vector of group standard deviations for a column.

batch_shift

A vector of batch means in a column.

batch_scale

A vector of batch standard deviations within a column.

group_weights

A K x B matrix of the expected proportion of N in each group in each batch.

batch_weights

A vector of the expected proportion of N in each batch.

dfs

A K-vector of the group specific degrees of freedom.

frac_known

The number of items with known labels.

Value

A list of 5 objects; the data generated from the groups with and without batch effects, the label indicating the generating group, the batch label and the vector indicating training versus test.

Examples

N <- 500
P <- 2
K <- 2
B <- 5
mean_dist <- 4
batch_dist <- 0.3
group_means <- seq(1, K) * mean_dist
batch_shift <- rnorm(B, mean = batch_dist, sd = batch_dist)
std_dev <- rep(2, K)
batch_var <- rep(1.2, B)
group_weights <- rep(1 / K, K)
batch_weights <- rep(1 / B, B)
dfs <- c(4, 7)
my_data <- generateBatchDataMVT(
  N,
  P,
  group_means,
  std_dev,
  batch_shift,
  batch_var,
  group_weights,
  batch_weights,
  dfs
)