{"id":26919186,"url":"https://github.com/dzakwanalifi/reglins","last_synced_at":"2025-07-09T01:42:35.870Z","repository":{"id":246090927,"uuid":"820072980","full_name":"dzakwanalifi/regLins","owner":"dzakwanalifi","description":"regLins is an R package designed for performing linear regression analysis using various optimization methods. 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You can download it from [CRAN](https://cran.r-project.org/).\n\n### Install devtools Package\n\nIf you haven't already installed the `devtools` package, do so by running:\n\n```r\ninstall.packages(\"devtools\")\n```\n\n### Install regLins from GitHub\n\nYou can install the `regLins` package directly from GitHub using the `devtools` package:\n\n```r\nlibrary(devtools)\ninstall_github(\"dzakwanalifi/regLins\")\n```\n\n## Usage\n\n### Linear Regression with Optimization\n\nThe `regLin` function allows you to perform linear regression using different optimization methods.\n\n#### Example Usage\n\n```r\nlibrary(regLins)\n\n# Generate some example data\nset.seed(123)\ny \u003c- rnorm(100)\nX \u003c- cbind(1, rnorm(100))\n\n# Perform regression using the regLin function\nmodel \u003c- regLin(y, X, method = \"kuadrat terkecil\")\n\n# Summarize the model\nsummary(model)\n```\n\n### Running the Shiny App\n\nThe `regLins` package includes a Shiny app for interactive analysis.\n\n#### Running the Shiny App\n\n```r\nlibrary(shiny)\nlibrary(regLins)\n\n# Run the Shiny app\nrunApp(system.file(\"shinyApp\", package = \"regLins\"))\n```\n\n#### Shiny App Interface\n\n1. **Upload File**: Allows you to upload a CSV or Excel file.\n2. **Select Variables**: Dropdown menus to select response and predictor variables.\n3. **Choose Method**: Option to select the optimization method.\n4. **Run Regression**: Button to run the regression analysis.\n5. **Summary Tab**: Displays a summary of the regression model.\n6. **Plot Tab**: Shows diagnostic plots of the regression model.\n\n## Detailed Function Documentation\n\n### regLin Function\n\nPerforms linear regression with optimization methods.\n\n#### Usage\n\n```r\nregLin(y, X, method = \"kuadrat terkecil\")\n```\n\n#### Arguments\n\n- `y`: A numeric vector of the response variable.\n- `X`: A numeric matrix of predictor variables.\n- `method`: The optimization method to be used (\"kuadrat terkecil\" or \"kemungkinan\").\n\n#### Value\n\nReturns an object of class `regLins`.\n\n### summary Function\n\nProvides a summary of the regression results.\n\n#### Usage\n\n```r\nsummary(object)\n```\n\n#### Arguments\n\n- `object`: An object of class `regLins`.\n\n### plot Function\n\nPlots diagnostic plots for the regression model.\n\n#### Usage\n\n```r\nplot(object)\n```\n\n#### Arguments\n\n- `object`: An object of class `regLins`.\n\n## Author\n\nMuhammad Dzakwan Alifi  \ndzakwan624@gmail.com\n\n## License\n\nThis package is licensed under the GPL-3 License.\n\n### Instructions for the User\n\n1. **Clone the Repository**: If you want to work directly with the source code or make contributions, you can clone the repository:\n   ```sh\n   git clone https://github.com/dzakwanalifi/regLins.git\n   ```\n\n2. **Issues and Contributions**: If you encounter any issues or want to contribute to the development of this package, feel free to open an issue or submit a pull request on GitHub.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdzakwanalifi%2Freglins","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdzakwanalifi%2Freglins","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdzakwanalifi%2Freglins/lists"}