import { OpenAssistantTool } from '@openassistant/utils';
import { z } from 'zod';
import { LinearRegressionResult, SpatialErrorResult, SpatialLagResult } from '@geoda/regression';
import { GetValues } from '../types';
export type SpatialRegressionFunctionArgs = z.ZodObject<{
    datasetName: z.ZodString;
    dependentVariable: z.ZodString;
    independentVariables: z.ZodArray<z.ZodString>;
    modelType: z.ZodEnum<['classic', 'spatial-lag', 'spatial-error']>;
    weightsId: z.ZodOptional<z.ZodString>;
}>;
export type SpatialRegressionLlmResult = {
    success: boolean;
    result?: string;
    error?: string;
};
export type SpatialRegressionAdditionalData = {
    datasetName: string;
    report: LinearRegressionResult | SpatialLagResult | SpatialErrorResult | null;
};
export type SpatialRegressionFunctionContext = {
    getValues: GetValues;
    config?: {
        theme?: string;
    };
};
/**
 * ## spatialRegression Tool
 *
 * This tool performs regression analysis with spatial data, accounting for spatial effects that may violate the independence assumption of classical regression.
 * It supports both classical and spatial regression models with proper diagnostics.
 *
 * ### Spatial Regression Models
 *
 * The tool supports three types of regression models:
 * - **classic**: Ordinary Least Squares (OLS) regression with spatial diagnostics
 * - **spatial-lag**: Spatial lag model accounting for spatial dependence in the dependent variable
 * - **spatial-error**: Spatial error model accounting for spatial dependence in the error term
 *
 * ### Parameters
 * - `datasetName`: Name of the dataset containing the variables
 * - `dependentVariable`: Name of the dependent variable (y)
 * - `independentVariables`: Array of independent variable names (x1, x2, ...)
 * - `modelType`: Type of regression model (see above)
 * - `weightsId`: ID of spatial weights matrix (required for spatial models)
 *
 * **Example user prompts:**
 * - "Can you run a spatial regression analysis on the housing data?"
 * - "Perform a spatial lag regression of revenue ~ population + income"
 * - "Run OLS regression with spatial diagnostics for crime rates"
 *
 * ### Example
 * ```typescript
 * import { spatialRegression } from "@openassistant/geoda";
 * import { convertToVercelAiTool } from "@openassistant/utils";
 *
 * const regressionTool = {
 *   ...spatialRegression,
 *   context: {
 *     getValues: async (datasetName: string, variableName: string) => {
 *       // Implementation to retrieve values from your data source
 *       return [100, 200, 150, 300, 250, 180, 220, 190, 280, 210];
 *     },
 *   },
 * };
 *
 * const result = await generateText({
 *   model: openai('gpt-4.1', { apiKey: key }),
 *   prompt: 'Can you run a spatial regression analysis of "revenue ~ population + income" on the data?',
 *   tools: { spatialRegression: convertToVercelAiTool(regressionTool) },
 * });
 * ```
 *
 * :::note
 * Please only use knowledge from Luc Anselin's GeoDa book and the GeoDa documentation to answer questions about spatial regression.
 * :::
 */
export declare const spatialRegression: OpenAssistantTool<SpatialRegressionFunctionArgs, SpatialRegressionLlmResult, SpatialRegressionAdditionalData, SpatialRegressionFunctionContext>;
export type SpatialRegressionTool = typeof spatialRegression;
type SpatialRegressionArgs = {
    datasetName: string;
    dependentVariable: string;
    independentVariables: string[];
    modelType: string;
    weightsId?: string;
};
export declare function isSpatialRegressionArgs(args: unknown): args is SpatialRegressionArgs;
export {};