Simulation of Multivariate Linear Model Data
Simulation of Multivariate Linear Model Data
Simulation Plot: The true beta, relevant component and eigen structure
Tidy Functions to make plotting easy
Extract Eigenvalues of predictors
Tidy covariance matrix
Function for data simulation
Simulation of Multivariate Linear Model Data
Simulation of Multivariate Linear Model data with response
Extract various sigma matrices
Prepare data for Plotting Covariance Matrix
Covariance between X and Y
Covariance between Z and W
Covariance between Z and Y
Extra test functions
Simulation Plot with ggplot: The true beta, relevant component and eig...
Function to create MBR-design.
A function to set up a design for a given set of factors with their sp...
Simulation of Multivariate Linear Model Data
Simulation of Multivariate Linear Model Data
Some helper function for simulation
Pipe operator
Plotting Functions
Plotting Covariance Matrix
Plot Covariance between predictor (components) and response (component...
A wrapper function for a simrel object
Prepare design for experiment from a list of simulation parameter
Researchers have been using simulated data from a multivariate linear model to compare and evaluate different methods, ideas and models. Additionally, teachers and educators have been using a simulation tool to demonstrate and teach various statistical and machine learning concepts. This package helps users to simulate linear model data with a wide range of properties by tuning few parameters such as relevant latent components. In addition, a shiny app as an 'RStudio' gadget gives users a simple interface for using the simulation function. See more on: Sæbø, S., Almøy, T., Helland, I.S. (2015) <doi:10.1016/j.chemolab.2015.05.012> and Rimal, R., Almøy, T., Sæbø, S. (2018) <doi:10.1016/j.chemolab.2018.02.009>.