https://github.com/dzakwanalifi/reglins
regLins is an R package designed for performing linear regression analysis using various optimization methods. It also provides an interactive Shiny application for a more dynamic analysis experience.
https://github.com/dzakwanalifi/reglins
data-analysis linear-regression optimization r shiny-app
Last synced: 12 months ago
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regLins is an R package designed for performing linear regression analysis using various optimization methods. It also provides an interactive Shiny application for a more dynamic analysis experience.
- Host: GitHub
- URL: https://github.com/dzakwanalifi/reglins
- Owner: dzakwanalifi
- Created: 2024-06-25T18:36:20.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-25T19:26:11.000Z (almost 2 years ago)
- Last Synced: 2024-06-26T21:10:08.823Z (almost 2 years ago)
- Topics: data-analysis, linear-regression, optimization, r, shiny-app
- Language: R
- Homepage: https://github.com/dzakwanalifi/regLins
- Size: 21.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# regLins
`regLins` is an R package for performing linear regression analysis with different optimization methods and provides a Shiny application for interactive analysis.
## Installation
### Prerequisites
Ensure you have R installed. You can download it from [CRAN](https://cran.r-project.org/).
### Install devtools Package
If you haven't already installed the `devtools` package, do so by running:
```r
install.packages("devtools")
```
### Install regLins from GitHub
You can install the `regLins` package directly from GitHub using the `devtools` package:
```r
library(devtools)
install_github("dzakwanalifi/regLins")
```
## Usage
### Linear Regression with Optimization
The `regLin` function allows you to perform linear regression using different optimization methods.
#### Example Usage
```r
library(regLins)
# Generate some example data
set.seed(123)
y <- rnorm(100)
X <- cbind(1, rnorm(100))
# Perform regression using the regLin function
model <- regLin(y, X, method = "kuadrat terkecil")
# Summarize the model
summary(model)
```
### Running the Shiny App
The `regLins` package includes a Shiny app for interactive analysis.
#### Running the Shiny App
```r
library(shiny)
library(regLins)
# Run the Shiny app
runApp(system.file("shinyApp", package = "regLins"))
```
#### Shiny App Interface
1. **Upload File**: Allows you to upload a CSV or Excel file.
2. **Select Variables**: Dropdown menus to select response and predictor variables.
3. **Choose Method**: Option to select the optimization method.
4. **Run Regression**: Button to run the regression analysis.
5. **Summary Tab**: Displays a summary of the regression model.
6. **Plot Tab**: Shows diagnostic plots of the regression model.
## Detailed Function Documentation
### regLin Function
Performs linear regression with optimization methods.
#### Usage
```r
regLin(y, X, method = "kuadrat terkecil")
```
#### Arguments
- `y`: A numeric vector of the response variable.
- `X`: A numeric matrix of predictor variables.
- `method`: The optimization method to be used ("kuadrat terkecil" or "kemungkinan").
#### Value
Returns an object of class `regLins`.
### summary Function
Provides a summary of the regression results.
#### Usage
```r
summary(object)
```
#### Arguments
- `object`: An object of class `regLins`.
### plot Function
Plots diagnostic plots for the regression model.
#### Usage
```r
plot(object)
```
#### Arguments
- `object`: An object of class `regLins`.
## Author
Muhammad Dzakwan Alifi
dzakwan624@gmail.com
## License
This package is licensed under the GPL-3 License.
### Instructions for the User
1. **Clone the Repository**: If you want to work directly with the source code or make contributions, you can clone the repository:
```sh
git clone https://github.com/dzakwanalifi/regLins.git
```
2. **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.