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GroupEff_par_usage

Introduction

The GroupEff_par function estimates group effects using embeddings and structured input data. This vignette demonstrates the usage of the GroupEff_par function with example data included in the package.

Load the Required Library

Ensure the MUGS package is loaded before running the example:

library(MUGS)

Load the Data

Load the required datasets for the example:

# Load required data
data(S.1)
data(S.2)
data(X.group.source)
data(X.group.target)
data(U.1)
data(U.2)

Prepare Variables

Prepare the variables required for the GroupEff_par function:

# Extract names and create name lists
names.list.1 <- rownames(S.1)
names.list.2 <- rownames(S.2)
full.name.list <- c(names.list.1, names.list.2)

# Initialize beta matrix
beta.names.1 <- unique(c(colnames(X.group.source), colnames(X.group.target)))
beta.int <- matrix(0, 400, 10)  # Replace with appropriate dimensions
rownames(beta.int) <- beta.names.1

Run the Function

Run the GroupEff_par function:

  GroupEff_par.out <- GroupEff_par(
    S.MGB = S.1, 
    S.BCH = S.2, 
    n.MGB = 2000, 
    n.BCH = 2000, 
    U.MGB = U.1, 
    U.BCH = U.2, 
    V.MGB = U.1, 
    V.BCH = U.2, 
    X.MGB.group = X.group.source, 
    X.BCH.group = X.group.target,
    n.group = 400, 
    name.list = full.name.list, 
    beta.int = beta.int, 
    lambda = 0, 
    p = 10, 
    n.core = 2
  )

Examine the Output

Explore the structure and key components of the output:

# View structure of the output
str(GroupEff_par.out)

# Print specific components of the result
cat("\nEstimated Group Effects:\n")
print(GroupEff_par.out$effects[1:5, 1:3])  # Show the first 5 rows and 3 columns of effects

cat("\nRegularization Path:\n")
print(GroupEff_par.out$path)

Notes

  1. Custom Parameters: Modify parameters like n.MGB, n.BCH, p, and lambda to test different scenarios.
  2. Data Preparation: Ensure datasets (S.1, S.2, U.1, U.2, etc.) are correctly loaded and aligned.
  3. Output: Key components include the estimated group effects matrix and regularization path.

Summary

This vignette demonstrated how to use the GroupEff_par function for estimating group effects. Adjust input parameters and datasets to test different scenarios and interpret the output components for your analysis.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.