151 lines
6.4 KiB
TypeScript
151 lines
6.4 KiB
TypeScript
/**
|
|
* Factory functions for standard statistics strings
|
|
*/
|
|
export declare abstract class Stats {
|
|
/**
|
|
* The count (number) of data points used for the statistical calculation.
|
|
*/
|
|
static readonly SAMPLE_COUNT = "SampleCount";
|
|
/**
|
|
* The value of Sum / SampleCount during the specified period.
|
|
*/
|
|
static readonly AVERAGE = "Average";
|
|
/**
|
|
* All values submitted for the matching metric added together.
|
|
* This statistic can be useful for determining the total volume of a metric.
|
|
*/
|
|
static readonly SUM = "Sum";
|
|
/**
|
|
* The lowest value observed during the specified period.
|
|
* You can use this value to determine low volumes of activity for your application.
|
|
*/
|
|
static readonly MINIMUM = "Minimum";
|
|
/**
|
|
* The highest value observed during the specified period.
|
|
* You can use this value to determine high volumes of activity for your application.
|
|
*/
|
|
static readonly MAXIMUM = "Maximum";
|
|
/**
|
|
* Interquartile mean (IQM) is the trimmed mean of the interquartile range, or the middle 50% of values.
|
|
*
|
|
* It is equivalent to `trimmedMean(25, 75)`.
|
|
*/
|
|
static readonly IQM = "IQM";
|
|
/**
|
|
* Percentile indicates the relative standing of a value in a dataset.
|
|
*
|
|
* Percentiles help you get a better understanding of the distribution of your metric data.
|
|
*
|
|
* For example, `p(90)` is the 90th percentile and means that 90% of the data
|
|
* within the period is lower than this value and 10% of the data is higher
|
|
* than this value.
|
|
*/
|
|
static percentile(percentile: number): string;
|
|
/**
|
|
* A shorter alias for `percentile()`.
|
|
*/
|
|
static p(percentile: number): string;
|
|
/**
|
|
* Trimmed mean (TM) is the mean of all values that are between two specified boundaries.
|
|
*
|
|
* Values outside of the boundaries are ignored when the mean is calculated.
|
|
* You define the boundaries as one or two numbers between 0 and 100, up to 10
|
|
* decimal places. The numbers are percentages.
|
|
*
|
|
* - If two numbers are given, they define the lower and upper bounds in percentages,
|
|
* respectively.
|
|
* - If one number is given, it defines the upper bound (the lower bound is assumed to
|
|
* be 0).
|
|
*
|
|
* For example, `tm(90)` calculates the average after removing the 10% of data
|
|
* points with the highest values; `tm(10, 90)` calculates the average after removing the
|
|
* 10% with the lowest and 10% with the highest values.
|
|
*/
|
|
static trimmedMean(p1: number, p2?: number): string;
|
|
/**
|
|
* A shorter alias for `trimmedMean()`.
|
|
*/
|
|
static tm(p1: number, p2?: number): string;
|
|
/**
|
|
* Winsorized mean (WM) is similar to trimmed mean.
|
|
*
|
|
* However, with winsorized mean, the values that are outside the boundary are
|
|
* not ignored, but instead are considered to be equal to the value at the
|
|
* edge of the appropriate boundary. After this normalization, the average is
|
|
* calculated. You define the boundaries as one or two numbers between 0 and
|
|
* 100, up to 10 decimal places.
|
|
*
|
|
* - If two numbers are given, they define the lower and upper bounds in percentages,
|
|
* respectively.
|
|
* - If one number is given, it defines the upper bound (the lower bound is assumed to
|
|
* be 0).
|
|
*
|
|
* For example, `tm(90)` calculates the average after removing the 10% of data
|
|
* points with the highest values; `tm(10, 90)` calculates the average after removing the
|
|
* 10% with the lowest and 10% with the highest values.
|
|
*
|
|
* For example, `wm(90)` calculates the average while treating the 10% of the
|
|
* highest values to be equal to the value at the 90th percentile.
|
|
* `wm(10, 90)` calculates the average while treaing the bottom 10% and the
|
|
* top 10% of values to be equal to the boundary values.
|
|
*/
|
|
static winsorizedMean(p1: number, p2?: number): string;
|
|
/**
|
|
* A shorter alias for `winsorizedMean()`.
|
|
*/
|
|
static wm(p1: number, p2?: number): string;
|
|
/**
|
|
* Trimmed count (TC) is the number of data points in the chosen range for a trimmed mean statistic.
|
|
*
|
|
* - If two numbers are given, they define the lower and upper bounds in percentages,
|
|
* respectively.
|
|
* - If one number is given, it defines the upper bound (the lower bound is assumed to
|
|
* be 0).
|
|
*
|
|
* For example, `tc(90)` returns the number of data points not including any
|
|
* data points that fall in the highest 10% of the values. `tc(10, 90)`
|
|
* returns the number of data points not including any data points that fall
|
|
* in the lowest 10% of the values and the highest 90% of the values.
|
|
*/
|
|
static trimmedCount(p1: number, p2?: number): string;
|
|
/**
|
|
* Shorter alias for `trimmedCount()`.
|
|
*/
|
|
static tc(p1: number, p2?: number): string;
|
|
/**
|
|
* Trimmed sum (TS) is the sum of the values of data points in a chosen range for a trimmed mean statistic.
|
|
* It is equivalent to `(Trimmed Mean) * (Trimmed count)`.
|
|
*
|
|
* - If two numbers are given, they define the lower and upper bounds in percentages,
|
|
* respectively.
|
|
* - If one number is given, it defines the upper bound (the lower bound is assumed to
|
|
* be 0).
|
|
*
|
|
* For example, `ts(90)` returns the sum of the data points not including any
|
|
* data points that fall in the highest 10% of the values. `ts(10, 90)`
|
|
* returns the sum of the data points not including any data points that fall
|
|
* in the lowest 10% of the values and the highest 90% of the values.
|
|
*/
|
|
static trimmedSum(p1: number, p2?: number): string;
|
|
/**
|
|
* Shorter alias for `trimmedSum()`.
|
|
*/
|
|
static ts(p1: number, p2?: number): string;
|
|
/**
|
|
* Percentile rank (PR) is the percentage of values that meet a fixed threshold.
|
|
*
|
|
* - If two numbers are given, they define the lower and upper bounds in absolute values,
|
|
* respectively.
|
|
* - If one number is given, it defines the upper bound (the lower bound is assumed to
|
|
* be 0).
|
|
*
|
|
* For example, `percentileRank(300)` returns the percentage of data points that have a value of 300 or less.
|
|
* `percentileRank(100, 2000)` returns the percentage of data points that have a value between 100 and 2000.
|
|
*/
|
|
static percentileRank(v1: number, v2?: number): string;
|
|
/**
|
|
* Shorter alias for `percentileRank()`.
|
|
*/
|
|
static pr(v1: number, v2?: number): string;
|
|
}
|