pECV (version 1.0.1)

generate_continuous_data_miss: Generate continuous data with missing values

Description

Generate simulated data from a Gaussian factor model with missing values.

Usage

generate_continuous_data_miss(
  n = 100,
  p = 50,
  q = 3,
  noise_sd = 1,
  miss_prop = 0.05
)

Value

A named list with components:

resp

Numeric matrix (n x p). Generated data with missing values (NA).

resp_complete

Numeric matrix (n x p). Complete data before missingness.

true_q

Integer. True number of factors used in simulation.

theta_true

Numeric matrix (n x (q+1)). True latent factor scores with intercept.

A_true

Numeric matrix (p x (q+1)). True factor loadings.

miss_prop

Numeric. Proportion of entries set to missing.

Arguments

n

Integer. Number of observations.

p

Integer. Number of variables.

q

Integer. True number of latent factors.

noise_sd

Numeric. Standard deviation of Gaussian noise.

miss_prop

Numeric in (0,1). Proportion of missing values (default 0.05).