---
title: "Evaluation_sim_usage"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Evaluation_sim_usage}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)
```

## Introduction

The `evaluation_sim` function is used to evaluate the performance of group effect estimation algorithms under simulated conditions. This vignette demonstrates how to use the `evaluation_sim` function with example data provided in the package.

---

## Load the Required Library

Ensure the `MUGS` package is loaded before running the example:

```{r setup}
library(MUGS)
```

---

## Load Example Data

Load the example data required for the `evaluation_sim` function:

```{r load_data}
data(pairs.rel.EV)
data(U.2)
```
---

## Run the Evaluation Simulation

Run the `evaluation_sim` function to evaluate the performance based on the provided data:

```{r run_simulation}
# Evaluate simulation
evaluation_results <- evaluation.sim(pairs.rel.EV, U.2)
```

---

## Examine the Output

Explore the structure and key components of the output:

```{r examine_output}
# View the structure of the output
str(evaluation_results)

# Display first few rows of the results
cat("\nEvaluation Results (first 5 rows):\n")
print(head(evaluation_results, 5))
```

---

## Notes

1. **Input Data**: Ensure that `pairs.rel.EV` and `U.2` are properly formatted and loaded before running the function.
2. **Output Structure**: The output typically includes evaluation metrics and processed results for further analysis.

---

## Summary

This vignette demonstrated the use of the `evaluation_sim` function for evaluating group effect estimation. Customize the input data and analyze the output to assess the performance of your algorithms.
