als-statistics
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Modular JS statistics toolkit for Node.js and the browser: descriptive stats, correlations (Pearson/Spearman/Kendall), t-tests & ANOVA (Student/Welch), reliability (Cronbach’s alpha), regression (linear/logistic), clustering (DBSCAN/HDBSCAN), and table/co
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Markdown
<title>Linear Regression (Core)</title>
<description>## Class: `Regression.LinearRegression`</description>
<keywords>linear, regression, core, class, regression.linearregression, public, fields, getters, methods, js, new, table</keywords>
# Linear Regression (Core)
## Class: `Regression.LinearRegression`
**Constructor**
```js
new Regression.LinearRegression(table: Record<string, number[]>, yName: string, xNames: string[], stepIndex: number)
```
### Public fields / getters
- `coefficients: number[]` – `[Intercept, β1, …]`.
- `y: number[]`, `X: number[][]`, `yHat: number[]`
- `residuals: number[]`
- `r2: number`
- `standardErrors: number[]`
- `pValues: number[]`
- `n: number`, `k: number` (obs & parameters)
- `result: { step, n, Variable, Coefficient, StdError, pValue }`
- `htmlTable: string`
### Methods
- `calculate(): this`
- `predict(X: number[][]): number[]`