Questions tagged [disaggregation]

Increasing the resolution of data, going from "lumpy" data to data on a finer scale. Especially used for time or spatial disaggregation, for example going from yearly to monthly data.

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Chow-Lin Time Series Disaggregation

Hy, I am working on a time series with yearly observations starting from 1995. Since I wanted to forecast the next values with ARIMA methods, I thought it was more appropriate to get quarterly data ...
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Regressions with different periodicity

I am trying to estimate a regression with variables of different periodicity. The dependent variable is given monthly, whereas most other independent variables are also given monthly, but some are ...
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Modeling Disaggregation

I'm going to try to explain my problem as simply as possible, but if there's any clarification needed please let me know. Essentially, I'm predicting that I'm going to sell 100 units total across 5 ...
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How to reconstruct moments from aggregated data?

Let $X_{1\ldots n}$ be a stochastic variable that is log-normal distributed, with parameters $\mu$ and $\sigma$. Now suppose all $X_i$ are aggregated into $Y_{1\ldots m}$ where $Y_1$ is the mean of ...
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Knowing the level of aggregate processes, how to get the levels of constituents?

I have a bunch of component processes $y_{it}$, where $i=1..n$. I can build reasonable time series models $y_{it}=f_i(y_{i,s<t},X_t)$, where $X_t$ - exogenous variables. These could be ARIMAX ...
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multivariate temporal disaggregation

I am trying to disaggregate quarterly data to monthly (currently without indicator series). I have tried denton, chow-lin, etc in the tempdisagg r package with no luck so far, mostly due to lack of ...
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Model that form relation between high frequency input and output variables, but observations are available at mixed frequency

I want to explore some forecasting models that form relation with daily output data and daily input data , but learns through monthly output data and daily input data. That means, output observations ...
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Temporal disaggregation: How to identify suitable indicator series?

I'm working on temporal disaggregation of economic time series (expecting to use the R package tempdisagg) and would like to use indicator series, but I have not been able to find out how to identify ...
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Issues when using independent variables from two levels for prediction on single level

This is my first question here and I want to make sure I am giving as much relevant background as possible, so please bear with me! I am analysing the factors influencing commute mode choice in ...
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30 views

Why is it important to realize that the high frequency is an integer multiple of the low frequency in all disaggregation methods available?

I was trying to disaggregate my monthly dataset to daily dataset using an indicator variable. I checked online and realized that there is an R package called tempdisagg available here https://cran.r-...
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De-aggregate data: statistically correct approaches?

Reading some research studies and there are interesting aggregated results. I want to plug it into a neural network (or similar) in order to categorise individual entries into alignment with what the ...