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It's not very clear to me why we need to "decompose" the time series. I understand that it can show a plot with 4 rows but I'm not sure what I'm supposed to be mindful of when looking at the decomposi…
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Is ist addative or multuplicative?
Needs to be decided based on the seasonality. If the variation of the seasonality is constant, then additive, otherwise multuplicative
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This is a fascinating lecture and I imagine it's going to be very useful for undergraduate macro. I think it's suitable for the introductory lecture series, even though it's more advanced than most.
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jstac updated
4 months ago
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> As an illustrative example, a single wind turbine can generate hundreds of data points every 20 ms for fault detection or prediction through a set of sophisticated operations against time series by …
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Submitting Author: Name (@pluflou)
Package Name: Solar Data Tools
One-Line Description of Package: Library of tools for analyzing photovoltaic power time-series data.
Repository Link (if existin…
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PyAF uses an **iterated one-step ahead forecasting**, that is , the same model (signal transformation + signal decomposition) forecast is iterated one-step at a time.
Other forecasting strategies d…
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# Phase 1: MVP Package
Develop a minimal package with the most important functions.
Use this guide: https://py-pkgs.org/03-how-to-package-a-python
## Priority 1 - Core Data and Data Frame Op…
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``` r
library(tidyverse)
library(fredr)
library(forecast)
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
library(lubridate)
# Set…
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```
Modular decomposition refers to the process of building a modular
decomposition tree. These can yield very interesting properties about
graphs (directed, undirected, and hypergraphs alike). Mo…
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```
Modular decomposition refers to the process of building a modular
decomposition tree. These can yield very interesting properties about
graphs (directed, undirected, and hypergraphs alike). Mo…