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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How to work with an aggregate value set for multiple items

I have a natural disasters dataset from EMDAT that records the impact of a disaster as an aggregate (Total) against locations as follows: Total affected Locations 10000 locationA locationB locationC ...
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Time series benchmarking/reconciliation and revisions - are there methods that minimise revisions?

I am using the tempdisagg R package for benchmarking quarterly time series to annual time series from different (more trusted) sources (by temporally disaggragating the annual data using the quarterly ...
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why the sum of two variables is insignificant while each of them are?

When I regress stock returns of period $t$ on stock ownership of period $t-1$, the coefficient on this lagged stock ownership is insignificant. However, when I disaggregate the lagged stock ownership ...
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Re-constructing regression coefficients from subgroup analysis results from randomized clinical trials

I'm looking at a common situation in medical research, where only aggregate results get published, but we'd really like to get information that is not directly provided. For a randomized controlled ...
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Changing frequency and the effect on autocorrelation

Say I have a model following an AR(1)-structure $x_t = \rho x_{t-1}+\epsilon_t$. This model is valid for hourly observations of $x$. With this assumption, what can be said about the distribution of $...
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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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Is there a name for applying estimation at a lower level of aggregation, and is it necessarily problematic?

Suppose you estimate a model using firm-level or state-level data and then apply the estimates at a lower level of aggregation, say at factory-level$^*$ or county-level. If it makes things easier, ...
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Which algorithm can I use for breaking down monthly forecast into daily forecasts / buckets?

I'm a trainee at a medical device distribution center. My internship project is to break down monthly forecast into daily forecasts / buckets. in the current situation the monthly forecast is broken ...
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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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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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Regression model with aggregated targets

Similar as in this self-answered question, I want to ask about possible approaches for modelling data with aggregated targets, i.e. things like $$ \bar y_{j[i]} = \alpha + \beta x_i + \varepsilon_i $$...
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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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temporal disaggregation time series using regression

I originally posted this question on stackoverflow and was recommended to post here instead. I am trying to derive high frequency data from low frequency data. I also have a number of other related ...
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Curve disaggregation with neural network

I have to extract a specific curve from an aggregate curve. An example is illustrated in the picture below, the blue curve is the aggregate curve, and I want to extract the red curve from the latter. ...
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How to split aggregated variance of one random variable into multiple random variables?

I apologize if this question is trivial, but I didn't come to a conclusion by myself. I have an aggregated forecast for a group of $n$ items, normally distributed with mean and standard deviation. $...
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Fit individual-level model on aggregate-level target-data

The task is to build a regression model for individuals. I have all the independent variables for each individual, but the dependent variable only as an aggregates on group-level. Lets say, I am ...
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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 ...
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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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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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Disaggregation of spatial autocorrelation parameter

I have data aggregated at state level. When I estimate a spatial autoregressive model such as $$y = \rho W y + X\beta + \epsilon$$ on this data, I see that the autoregressive parameter $\rho$ is ...
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Should I use aggregate or disaggregate data?

I have this dataset of flows: ...
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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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Forecasting high frequency variable with low frequency predictor

Newbie here to forecasting and I have a very basic question. I have 2 distinct time-series data. Time Series A is Weekly (High frequency) Time Series B is Monthly (Low frequency) I need to forecast ...
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How do you choose a unit of analysis (level of aggregation) in a time series?

If you can measure a time series of observations at any level of precision in time, and your goal of the study is to identify a relationship between X and Y, is there any empirical justification for ...
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