public static double standardErrorOfMean(double[] a) { return stdev(a) / Math.sqrt(a.length); }
/** * Returns the standard deviation of a vector of doubles. Any values which * are NaN or infinite are ignored. If the vector contains fewer than two * values, 1.0 is returned. */ public static double safeStdev(double[] v) { double[] u = filterNaNAndInfinite(v); if (numRows(u) < 2) return 1.0; return stdev(u); }
/** * Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. * If standard deviation is 0.0, throws a RuntimeException. */ public static void standardize(double[] a) { double m = mean(a); if (Double.isNaN(m)) { throw new RuntimeException("Can't standardize array whose mean is NaN"); } double s = stdev(a); if (s == 0.0 || Double.isNaN(s)) { throw new RuntimeException("Can't standardize array whose standard deviation is 0.0 or NaN"); } addInPlace(a, -m); // subtract mean multiplyInPlace(a, 1.0/s); // divide by standard deviation }
public static double standardErrorOfMean(double[] a) { return stdev(a) / Math.sqrt(a.length); }
public static double standardErrorOfMean(double[] a) { return stdev(a) / Math.sqrt(a.length); }
public static double standardErrorOfMean(double[] a) { return stdev(a) / Math.sqrt(a.length); }
public static double standardErrorOfMean(double[] a) { return stdev(a) / Math.sqrt(a.length); }
/** * Returns the standard deviation of a vector of doubles. Any values which * are NaN or infinite are ignored. If the vector contains fewer than two * values, 1.0 is returned. */ public static double safeStdev(double[] v) { double[] u = filterNaNAndInfinite(v); if (numRows(u) < 2) return 1.0; return stdev(u); }
/** * Returns the standard deviation of a vector of doubles. Any values which * are NaN or infinite are ignored. If the vector contains fewer than two * values, 1.0 is returned. */ public static double safeStdev(double[] v) { double[] u = filterNaNAndInfinite(v); if (numRows(u) < 2) return 1.0; return stdev(u); }
/** * Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. * If standard deviation is 0.0, throws a RuntimeException. */ public static void standardize(double[] a) { double m = mean(a); if (Double.isNaN(m)) { throw new RuntimeException("Can't standardize array whose mean is NaN"); } double s = stdev(a); if (s == 0.0 || Double.isNaN(s)) { throw new RuntimeException("Can't standardize array whose standard deviation is 0.0 or NaN"); } addInPlace(a, -m); // subtract mean multiplyInPlace(a, 1.0/s); // divide by standard deviation }
/** * Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. * If standard deviation is 0.0, throws an RuntimeException. */ public static void standardize(double[] a) { double m = mean(a); if (Double.isNaN(m)) throw new RuntimeException("Can't standardize array whose mean is NaN"); double s = stdev(a); if(s == 0.0 || Double.isNaN(s)) throw new RuntimeException("Can't standardize array whose standard deviation is 0.0 or NaN"); addInPlace(a, -m); // subtract mean multiplyInPlace(a, 1.0/s); // divide by standard deviation }
/** * Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. * If standard deviation is 0.0, throws a RuntimeException. */ public static void standardize(double[] a) { double m = mean(a); if (Double.isNaN(m)) { throw new RuntimeException("Can't standardize array whose mean is NaN"); } double s = stdev(a); if (s == 0.0 || Double.isNaN(s)) { throw new RuntimeException("Can't standardize array whose standard deviation is 0.0 or NaN"); } addInPlace(a, -m); // subtract mean multiplyInPlace(a, 1.0/s); // divide by standard deviation }
/** * Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. * If standard deviation is 0.0, throws a RuntimeException. */ public static void standardize(double[] a) { double m = mean(a); if (Double.isNaN(m)) { throw new RuntimeException("Can't standardize array whose mean is NaN"); } double s = stdev(a); if (s == 0.0 || Double.isNaN(s)) { throw new RuntimeException("Can't standardize array whose standard deviation is 0.0 or NaN"); } addInPlace(a, -m); // subtract mean multiplyInPlace(a, 1.0/s); // divide by standard deviation }
/** * Returns the standard deviation of a vector of doubles. Any values which * are NaN or infinite are ignored. If the vector contains fewer than two * values, 1.0 is returned. */ public static double safeStdev(double[] v) { double[] u = filterNaNAndInfinite(v); if (numRows(u) < 2) return 1.0; return stdev(u); }
/** * Returns the standard deviation of a vector of doubles. Any values which * are NaN or infinite are ignored. If the vector contains fewer than two * values, 1.0 is returned. */ public static double safeStdev(double[] v) { double[] u = filterNaNAndInfinite(v); if (numRows(u) < 2) return 1.0; return stdev(u); }