Weighted |
public class WeightedDescriptiveStatistics
The WeightedDescriptiveStatistics type exposes the following members.
| Name | Description | |
|---|---|---|
| WeightedDescriptiveStatistics(IEnumerableTupleDouble, Double, Boolean) | Initializes a new instance of the WeightedDescriptiveStatistics class. | |
| WeightedDescriptiveStatistics(IEnumerableValueTupleDouble, Double, Boolean) | Initializes a new instance of the WeightedDescriptiveStatistics class. |
| Name | Description | |
|---|---|---|
| Count | Gets the size of the sample. | |
| EffectiveSampleSize | The Kish's effective sample size https://en.wikipedia.org/wiki/Effective_sample_size | |
| Kurtosis | Gets the unbiased estimator of the population excess kurtosis using the G_2 estimator. | |
| Maximum | Gets the maximum sample value. | |
| Mean | Gets the sample mean. | |
| Minimum | Gets the minimum sample value. | |
| Skewness | Gets the unbiased estimator of the population skewness. | |
| StandardDeviation | Gets the unbiased population standard deviation (on a dataset of size N will use an N-1 normalizer). | |
| TotalWeight | Gets the total weight. When used with unweighted data, returns the number of samples. | |
| Variance | Gets the unbiased population variance estimator (on a dataset of size N will use an N-1 normalizer). |
| Name | Description | |
|---|---|---|
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
| Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
| GetHashCode | Serves as the default hash function. (Inherited from Object) | |
| GetType | Gets the Type of the current instance. (Inherited from Object) | |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
| ToString | Returns a string that represents the current object. (Inherited from Object) |