8000 Add a smoothing example, multivariate with missing data and extreme data by jayzer · Pull Request #158 · pykalman/pykalman · GitHub
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Add a smoothing example, multivariate with missing data and extreme data #158

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Add a smoothing example, multivariate with missing data and extreme data #158

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@jayzer jayzer commented May 8, 2025

Practical example of using pykalman to smooth data. Interactive example using Jupyter Notebook format. Includes code comments and visualization to view the effects of Kalman Filter smoothing on example data.

jayzer and others added 4 commits May 8, 2025 19:55
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Added an example of a use case, multivariable, with extreme data and missing data.
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Merge pull request #1 from jayzer/jayzer-jupyter-examples
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Add: Example - Multivariate Kalman Filter with Missing Data
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Add: Multivariate Kalman Filter with Rolling Window Example
ee42dea 
Example use case of Multivariate Kalman Filter with a rolling window in Jupyter Notebook format.
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Merge pull request #2 from jayzer/jayzer-jupyter-examples
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Add: Multivariate Kalman Filter with Rolling Window Example
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jayzer commented May 9, 2025

Multivariate Kalman Filter Example
First example demonstrates a basic use case of Kalman Filter use on data with ten variables, extreme values, and missing values.

Multivariate Kalman Filter with Rolling Window Example
Second example demonstrates how to apply a Multivariate Kalman Filter to smooth noisy time-series data using a rolling window approach. It covers the following:

Topics covered in the examples:
Simulating data with noise, outliers, and missing values.
Initializing and training the Kalman Filter.
Implementing a rolling window for retraining and smoothing.
Visualizing the results.
Illustration of how to use the pykalman library in a rolling window use case. Comments include explanations of how to use package for data imputation, outlier handling, and dealing with missing values.

@fkiraly fkiraly mentioned this pull request May 11, 2025
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fkiraly commented May 15, 2025

closed in favour of #159, see discussion there

@fkiraly fkiraly closed this May 15, 2025
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