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Is there a multi-dimensional time series data analysis using GPU instead Dask Distributed MSTUMPED?
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Here is a summary of functionality from intense-qc and its extension for sub-hourly data as a basis for discussion of what could be added to pypwsqc:
Edit:
* strikethrough bullet points are rejec…
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1) Algorithm of stationaryization of time series consists of the following:
- A log transformation of feature variables to make data as "normal" as possible and make the statistical analysis res…
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hello i am trying to use the time_bucket_gapfill function but it does not work as expected.
i created a query like describe in this blog article:
https://blog.timescale.com/blog/sql-functions-for-…
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Time series analysis is a popular machine learning technique for forecasting trends of time-dependent variables such as stock price, GDP, and quarterly sales. Given the popularity (https://github.com/…
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Hi there,
I am working on time series data (Illumina raw reads quantified using Salmon) and ran into the following error:
```
Error in dynGENIE3(TS.data2, time.points2) :
NA/NaN/Inf in fore…
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Hello,
@jjonkman
I referred to the report “Offshore Code Comparison Collaboration(OC3) for IEA Task 23 Offshore Wind Technology and Deployment(NREL/TP-5000-48191)” that you wrote.
Your reports …
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#### Learning Goals
Learn the ARIMA models for time series season/trend analysis and forecast.
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> The primary goal of a longitudinal study is to characterise the change in response over time and the factors that influence change. [fitzmaurice2012applied]
> Clustered data can arise from random…
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Here's a plan to enhance TxtAI with geospatial and temporal search capabilities:
**1. Extend indexing for geospatial data:**
- Use GeoPandas for geospatial data handling, as it integrates well …