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Statistical hypothesis tests based on Matrix data.

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package se.alipsa.groovy.stats

import se.alipsa.groovy.matrix.Matrix

/**
 * Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation
 * procedures (such as the "variation" among and between groups) used to analyze the differences among means.
 * ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance,
 * where the observed variance in a particular variable is partitioned into components attributable to
 * different sources of variation. In its simplest form, ANOVA provides a statistical test of whether
 * two or more population means are equal, and therefore generalizes the t-test beyond two means.
 * In other words, the ANOVA is used to test the difference between two or more means.
 */
class Anova {

  static AnovaResult aov(Matrix data, List colNames) {
    Map> d = [:]
    colNames.each {
      String colName = it
      d.put(colName, data[colName] as List)
    }
    return aov(d)
  }

  /**
   * Implements one-way ANOVA (analysis of variance) statistics.
   *
   */
  static AnovaResult aov(Map> data) {
    if (data.size() < 2) {
      throw new IllegalArgumentException("data must contain at least 2 groups (found only ${data.size()} groups")
    }
    def result = new AnovaResult()
    // TODO implement me!
    return result
  }

  static class AnovaResult {

  }
}