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simrel (version 2.0)

Simulation of Multivariate Linear Model Data

Description

Simulate multivariate linear model data is useful in research and education weather for comparison or create data with specific properties. This package lets user to simulate linear model data of wide range of properties with few tuning parameters. The package also consist of function to create plots for the simulation objects and A shiny app as RStudio gadget. It can be a handy tool for model comparison, testing and many other purposes.

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Version

Install

install.packages('simrel')

Monthly Downloads

249

Version

2.0

License

GPL-3 | file LICENSE

Maintainer

Raju Rimal

Last Published

April 1st, 2019

Functions in simrel (2.0)

cov_zw

Covariance between Z and W
plot_beta

Plotting Functions
prepare_design

Prepare design for experiment from a list of simulation parameter
simrel

Simulation of Multivariate Linear Model Data
cov_mat

Extract various sigma matrices
plot_cov

Plotting Covariance Matrix
tidy_lambda

Extract Eigenvalues of predictors
cov_plot_data

Prepare data for Plotting Covariance Matrix
tidy_sigma

Tidy covariance matrix
parse_parm

Some helper function for simulation
%>%

Pipe operator
cov_zy

Covariance between Z and Y
expect_subset

Extra test functions
AppSimrel

Simulation of Multivariate Linear Model Data
bisimrel

Simulation of Multivariate Linear Model data with response
plot_covariance

Plot Covariance between predictor (components) and response (components)
ggsimrelplot

Simulation Plot with ggplot: The true beta, relevant component and eigen structure
plot_simrel

A wrapper function for a simrel object
unisimrel

Function for data simulation
mbrd

Function to create MBR-design.
mbrdsim

A function to set up a design for a given set of factors with their specific levels using the MBR-design method.
multisimrel

Simulation of Multivariate Linear Model Data
simrelplot

Simulation Plot: The true beta, relevant component and eigen structure
tidy_beta

Tidy Functions to make plotting easy
cov_xy

Covariance between X and Y