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Descriptive statistics such as mean, geometric mean, maximum, minimum, sample standard deviation and standard error, median, mode, coefficient of variation, and linear regression. Written for various data type arrays

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akkoyun/Statistical

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Statistical Library ^V2.5^

GitHub release (latest by date) arduino-library-badge Visits Badge GitHub stars Updated Badge PlatformIO Registry Check Arduino Compile Examples Spell Check

Build - 02.05.00

Abstract

Descriptive statistics for Arduino float arrays

We developed this library to help quickly accomplish median and mode filtering when collecting sensor data. Functions in this library operate on an array of float variables, of dimension "m", and return the corresponding statistic. This library was originally created for a data smoothing strategy for float variables. Using a median or mode filtering strategy (opposed to mean filtering) is better at removing spikes from aberrant readings.

A bubble sort algorithm is also contained in this library which was necessary to calculate median and mode.

Array Statistics
Library calculate listed statistical parameters for fixed size arrays.
* Average
* Sum
* Max
* Min
* Sq_Sum
* Arithmetic_Average
* Geometric_Average
* RMS_Average
* Ext_RMS_Average
* Sigma_Average
* Quartile
* IQR
* Standard_Deviation
* Standard_Deviation_Error
* Variance
* Bubble_Sort
* Array
* Set_FILO_Size
* FILO_Add_Data
Stream Statistics
Library calculate listed statistical parameters for data streams.
* Data Count
* Arithmetic Average
* Minimum
* Maximum
Array Linear Regression
Library calculate listed statistical parameters for fixed size arrays.
* Slope
* Offset
* R2
Stream Linear Regression
Library calculate listed statistical parameters for data stream. User set the regression precision for calculating last n data regression.
* Slope
* Offset
* R2
Machine Learning Algorithm
This library will calculate slope of data according last n value. With these slope data system can learn sensor anomaly and make decision.

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Descriptive statistics such as mean, geometric mean, maximum, minimum, sample standard deviation and standard error, median, mode, coefficient of variation, and linear regression. Written for various data type arrays

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