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  3. Descriptive Statistics

Descriptive Statistics

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Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data; The main aim is to summarize a data set, rather than use the data to learn about the population that the data are thought to represent.

  • ACF - Autocorrelation Function
  • ACFCI - ACF Confidence Interval Function
  • PACF - Partial Autocorrelation
  • PACFCI - Partial Autocorrelation Confidence Interval
  • GED_XKURT - GED Excess-Kurtosis
  • TDIST_XKURT - Kurtosis of t-distribution
  • XCF - Cross Correlation Function
  • EWXCF - Exponential-Weighted Correlation
  • EWMA - Exponential Weighted Volatility
  • NxKDE - Calculates the kernel density estimate
  • GINI - Gini Coefficient
  • Hurst Exponent, Index, or Parameter
  • IQR - Interquartile Range
  • LRVar - Long-run Variance (Bartlett Kernel)
  • MAD - Median of Absolute Deviation
  • MD - Mean Absolute Difference
  • Quantile - Sample Quantile
  • RMD - Relative Mean Difference
  • RMS - Root Mean Square
  • HISTBIN - Histogram Bin
  • HISTBINS - Number of Histogram Bins
  • EDF - Empirical Distribution Function
  • NxHistogram - Frequency Distribution (Histogram)
  • KDE - Kernel Density Estimation
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