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https://github.com/borchehq/incstats
librstats is a C library for efficient online computation of statistics, such as for mean, variance, skewness and kurtosis.
https://github.com/borchehq/incstats
c central-moments rolling-average rolling-statistics running-statistics statistics
Last synced: about 4 hours ago
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librstats is a C library for efficient online computation of statistics, such as for mean, variance, skewness and kurtosis.
- Host: GitHub
- URL: https://github.com/borchehq/incstats
- Owner: borchehq
- License: apache-2.0
- Created: 2020-12-22T20:27:45.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2024-09-05T02:40:45.000Z (2 months ago)
- Last Synced: 2024-11-07T06:14:24.389Z (about 4 hours ago)
- Topics: c, central-moments, rolling-average, rolling-statistics, running-statistics, statistics
- Language: C
- Homepage:
- Size: 37.1 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# libincstats
**incstats** is a C library for efficiently computing running statistics, such as mean, variance, skewness, kurtosis, central moments, and finding the maximum and minimum values in a dataset. The library is designed to handle weighted data points, making it suitable for a wide range of applications.
## Status
[](https://github.com/borchehq/incstats/actions/workflows/ci.yml)
[](https://codecov.io/gh/borchehq/incstats)
[](https://app.codacy.com/gh/borchehq/incstats/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
## Features
- Compute running mean, variance, skewness, and kurtosis.
- Calculate central moments up to a specified order.
- Calculate standardized central moments up to a specified order.
- Track maximum and minimum values.
- Designed for efficiency and simplicity.
- Handles weighted data points.
## Installation
To build and install the library, you will need [CMake](https://cmake.org/) version 3.0 or higher. Follow the steps below:
1. Clone the repository:
```bash
git clone https://github.com/borchehq/incstats.git
cd incstats
```
2. Create a build directory and navigate into it:
```bash
mkdir build
cd build
```
3. Configure the project using CMake:
```bash
cmake ..
```
4. Build the project:
```bash
make
```
5. Run the tests (optional):
```bash
make test
```
6. Install the library:
```bash
sudo make install
```
## Usage
Include the incstats header files in your project to use the library functions.
Here is a brief overview of the available functions:
Running Mean
```C
inline void incstats_mean(double x, double w, double *buffer);
inline void incstats_mean_finalize(double *mean, double *buffer);
```
Running Variance
```C
inline void incstats_variance(double x, double w, double *buffer);
inline void incstats_variance_finalize(double *results, double *buffer);
```
Running Skewness
```C
inline void incstats_skewness(double x, double w, double *buffer);
inline void incstats_skewness_finalize(double *results, double *buffer);
```
Running Kurtosis
```C
inline void incstats_kurtosis(double x, double w, double *buffer);
inline void incstats_kurtosis_finalize(double *results, double *buffer);
```
Central Moments
```C
inline void incstats_central_moment(double x, double w, double *buffer, uint64_t p);
inline void incstats_central_moment_finalize(double *results, double *buffer, uint64_t p, bool standardize);
```
Maximum and Minimum
```C
inline void incstats_max(double x, double *max);
inline void incstats_min(double x, double *min);
```
**Important Note**
All functions for higher moments (e.g., kurtosis) will also compute all lower moments
(e.g., skewness, variance, and mean) in a single pass. This feature enhances performance
and reduces computational overhead, making it efficient to obtain all necessary statistical
measures with minimal passes through the data.
**Example Usage in C**
```C
#include
#include "incstats.h"
int main() {
double buffer[5] = {0}; // Initialize buffer for mean, variance, skewness, kurtosis
double data[20] = {5.0, 3.2, 4.1, 2.9, 6.5, 4.3, 5.1, 3.8, 4.6, 2.7,
3.3, 5.7, 4.9, 2.4, 3.6, 5.8, 4.0, 6.2, 3.4, 5.3};
double w = 1.0;
// Update statistics with new values
for (int i = 0; i < 20; ++i) {
incstats_kurtosis(data[i], w, buffer); // This will also update mean, variance, and skewness
}
// Finalize and get results
double results[4];
incstats_kurtosis_finalize(results, buffer);
printf("Mean: %f\n", results[0]);
printf("Variance: %f\n", results[1]);
printf("Skewness: %f\n", results[2]);
printf("Kurtosis: %f\n", results[3]);
return 0;
}
```
**Example Usage in C++**
```CXX
#include // Use C++ iostream for printing
// Include the C header file with extern "C"
extern "C" {
#include "incstats.h"
}
int main() {
double buffer[5] = {0}; // Initialize buffer for mean, variance, skewness, kurtosis
double data[20] = {5.0, 3.2, 4.1, 2.9, 6.5, 4.3, 5.1, 3.8, 4.6, 2.7,
3.3, 5.7, 4.9, 2.4, 3.6, 5.8, 4.0, 6.2, 3.4, 5.3};
double w = 1.0;
// Update statistics with new values
for (int i = 0; i < 20; ++i) {
incstats_kurtosis(data[i], w, buffer); // This will also update mean, variance, and skewness
}
// Finalize and get results
double results[4];
incstats_kurtosis_finalize(results, buffer);
std::cout << "Mean: " << results[0] << std::endl;
std::cout << "Variance: " << results[1] << std::endl;
std::cout << "Skewness: " << results[2] << std::endl;
std::cout << "Kurtosis: " << results[3] << std::endl;
return 0;
}
```
## License
This project is licensed under the Apache License, Version 2.0. You may obtain a copy of the License at:
http://www.apache.org/licenses/LICENSE-2.0
The full text of the license is available in the `LICENSE.txt` file in this repository.