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About This Document
About Summary Statistics
Algorithms and Interfaces in Summary Statistics
Common Usage Model of Summary Statistics Algorithms
Processing Data in Blocks
Detecting Outliers in Datasets
Dealing with Missing Observations
Computing Quantiles for Streaming Data
Bibliography
Estimating Raw and Central Moments and Sums, Skewness, Excess Kurtosis, Variation, and Variance-Covariance/Correlation/Cross-Product Matrix
Computing Median Absolute Deviation
Computing Mean Absolute Deviation
Computing Minimum/Maximum Values
Calculating Order Statistics
Estimating Quantiles
Estimating a Pooled/Group Variance-Covariance Matrices/Means
Estimating a Partial Variance-Covariance Matrix
Performing Robust Estimation of a Variance-Covariance Matrix
Detecting Multivariate Outliers
Handling Missing Values in Matrices of Observations
Parameterizing a Correlation Matrix
Sorting an Observation Matrix
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Algorithms and Interfaces in Summary Statistics
This section discusses different methods and usage specifics of the Summary Statistics algorithms. For some methods, interfaces are described. For details on the Summary Statistics API, see [MKLMan].
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See Also:
- Estimating Raw and Central Moments and Sums, Skewness, Excess Kurtosis, Variation, and Variance-Covariance/Correlation/Cross-Product Matrix
- Computing Median Absolute Deviation
- Computing Mean Absolute Deviation
- Computing Minimum/Maximum Values
- Calculating Order Statistics
- Estimating Quantiles
- Estimating a Pooled/Group Variance-Covariance Matrix
- Performing Robust Estimation of a Variance-Covariance Matrix
- Detecting Multivariate Outliers
- Handling Missing Values in Matrices of Observations
- Parameterizing a Correlation Matrix
- Sorting an Observation Matrix
- Estimating Raw and Central Moments and Sums, Skewness, Excess Kurtosis, Variation, and Variance-Covariance/Correlation/Cross-Product Matrix
- Computing Median Absolute Deviation
- Computing Mean Absolute Deviation
- Computing Minimum/Maximum Values
- Calculating Order Statistics
- Estimating Quantiles
- Estimating a Pooled/Group Variance-Covariance Matrices/Means
- Estimating a Partial Variance-Covariance Matrix
- Performing Robust Estimation of a Variance-Covariance Matrix
- Detecting Multivariate Outliers
- Handling Missing Values in Matrices of Observations
- Parameterizing a Correlation Matrix
- Sorting an Observation Matrix