gojiplus rmcp

WHAT IT CONNECTS

What gojiplus rmcp gives an AI Agent

• **Linear Regression:** Run linear models with optional robust standard errors.
• **Panel Data Analysis:** Estimate fixed effects, random effects, pooling, between, and first-difference models.
• **Instrumental Variables:** Build and estimate IV regression models.
• **Diagnostic Tests:** Assess heteroskedasticity, autocorrelation, and model misspecification.
• **Descriptive Statistics:** Generate summary statistics for datasets using R’s summary() functionality.
• **Correlation Analysis:** Compute Pearson or Spearman correlations between variables.
• **Group-By Aggregations:** Group data by specified columns and compute summary statistics using dplyr.
• **Resources:** Access reference documentation for various econometric techniques.
• **Prompts:** Use pre-defined prompt templates for common econometric analyses.
• Build the Docker image:
• Run the container:
• Launch Claude Desktop
• Open the MCP Servers panel
• Add a new server with the following configuration:
• Name: R Econometrics
• Transport: stdio
• Command: path/to/python r_econometrics_mcp.py
• (Or if using Docker): docker run -i r-econometrics-mcp
• `formula` (string): The regression formula (e.g., 'y ~ x1 + x2')
• `data` (object): Dataset as a dictionary/JSON object
• `robust` (boolean, optional): Whether to use robust standard errors
• `formula` (string): The regression formula (e.g., 'y ~ x1 + x2')
• `data` (object): Dataset as a dictionary/JSON object
• `index` (array): Panel index variables (e.g., ['individual', 'time'])
• `effect` (string, optional): Type of effects: 'individual', 'time', or 'twoways'
• `model` (string, optional): Model type: 'within', 'random', 'pooling', 'between', or 'fd'
• `formula` (string): The regression formula (e.g., 'y ~ x1 + x2')
• `data` (object): Dataset as a dictionary/JSON object
• `tests` (array): Tests to run (e.g., ['bp', 'reset', 'dw'])
• `formula` (string): The regression formula (e.g., 'y ~ x1 + x2 | z1 + z2')
• `data` (object): Dataset as a dictionary/JSON object
• `econometrics:formulas`: Information about common econometric model formulations
• `econometrics:diagnostics`: Reference for diagnostic tests
• `econometrics:panel_data`: Guide to panel data analysis in R