An R-based econometrics MCP server that provides advanced statistical modeling capabilities through R packages like plm, lmtest, and AER. Developed by goji+, the server enables AI assistants to perform complex econometric analyses including linear regression, panel data modeling, instrumental variables regression, and diagnostic testing across various research domains. Useful for researchers and data scientists seeking programmatic access to robust statistical modeling tools.
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OLS with robust standard errors, Rยฒ, p-values.
Binary classification with odds ratios and accuracy.
Calculate Pearson, Spearman, and Kendall correlations.
Autoregressive integrated moving average with forecasting.
Decompose a time series into trend, seasonal, and remainder components.
Perform ADF, KPSS, and Phillips-Perron tests for stationarity.
Create time-shifted variables for analysis.
Handle outliers by capping extreme values.
Create stationary series for time series analysis.
Perform Z-score, min-max, or robust scaling.
Conduct one-sample, two-sample, or paired t-tests.
Perform analysis of variance with Types I/II/III.
Conduct independence and goodness-of-fit tests.
Perform Shapiro-Wilk, Jarque-Bera, and Anderson-Darling tests.
Generate comprehensive descriptive statistics with grouping.
Detect outliers using IQR, Z-score, or Modified Z-score methods.
Create counts and percentages with sorting.
Perform fixed/random effects regression for longitudinal data.
Conduct 2SLS with endogeneity testing.
Model multivariate time series.
Perform unsupervised K-means clustering with validation.
Build classification and regression trees.
Utilize ensemble methods with variable importance.
Create correlation plots with trend lines.
Analyze distribution with density overlay.
Conduct quartile analysis with outlier detection.
Visualize temporal data.
Create matrix visualization of correlations.
Generate model validation plots.
Import CSV files with flexible parsing options.
Export data to CSV with formatting control.
Analyze and provide comprehensive data structure information.
Select data based on complex conditional criteria.