# Variogram Modeling Analysis AI Agent Connect

> Compute experimental variograms and fit spatial continuity models.

## Overview
- **Category:** data-science
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_90eLi7v2uwyo9H83WpXIUBCy4b6pbJDJCcgQIl6L/ai-agent-connect
- **Tags:** variogram, spatial-correlation, geostatistics, anisotropy, modeling

## Description

This MCP server provides tools for geostatistical analysis of spatial autocorrelation. It allows AI agents to calculate an experimental variogram using `compute_experimental_variogram`, fit mathematical models like spherical or exponential via `fit_variogram_model`, and detect directional variation with `detect_anisotropy`. It also provides a high-level overview of spatial structures through `get_spatial_continuity_summary`.

## Tools

### compute_experimental_variogram
Calculates the raw semivariance values for a set of spatial data points at specified intervals

### detect_anisotropy
Determines if the spatial correlation varies significantly by direction

### fit_variogram_model
Fits a mathematical model to the experimental variogram to derive continuous parameters

### get_spatial_continuity_summary
Provides a high-level overview of the spatial structure of the dataset

## Prompt Examples

**Prompt:** 
```
Calculate the experimental variogram for these points: [{'x': 0, 'y': 0, 'z': 10}, {'x': 1, 'y': 1, 'z': 12}, {'x': 2, 'y': 0, 'z': 11}] with a lag distance of 1 and max distance of 5.
```

**Response:** 
```
[{"lag": 1, "semivariance": 1.33, "pairCount": 2}, {"lag": 2, "semivariance": 0.67, "pairCount": 1}]
```

**Prompt:** 
```
Fit a spherical model to these experimental points: [{'lag': 1, 'semivariance': 0.5, 'pairCount': 10}, {'lag': 2, 'semivariance': 1.2, 'pairCount': 8}, {'lag': 3, 'semivariance': 1.8, 'pairCount': 5}].
```

**Response:** 
```
{"nugget": 0.1, "sill": 2.0, "range": 3.5, "modelType": "spherical"}
```

**Prompt:** 
```
Check for anisotropy in this dataset using azimuths 0 and 90 degrees.
```

**Response:** 
```
{"isAnisotropic": true, "anisotropyRatio": 0.65, "directionalRanges": [{"direction": 0, "range": 10.5}, {"direction": 90, "range": 6.8}]}
```

## Frequently Asked Questions

**What is the purpose of this server?**
It quantifies spatial correlation by calculating semivariance and fitting models to spatial data.

**How do I detect if my data has anisotropy?**
You can use the `detect_anisotropy` tool by providing your spatial data and a list of azimuth directions to test.

**Can I fit specific mathematical models?**
Yes, the `fit_variogram_model` tool supports various model types like spherical and exponential.