Questions tagged [forecasting]
Prediction of the future events. It is a special case of [prediction], in the context of [time-series].
3,952 questions
1
vote
0
answers
37
views
Designing a demand forecasting model with a dynamic daily update and a final horizon prediction — best practices to avoid leakage?
I am working on a demand forecasting problem for ferry vehicle capacity.
For each voyage, I have daily snapshots of the cumulative reservations from the opening date until departure day.
So each ...
0
votes
0
answers
9
views
Are there any other powerful optimization tools available besides the ABC and PSO algorithms? [duplicate]
What are other optimization tools that are powerful enough to improve the accuracy performance of the neural network model? Please give me recent tools that are powerful
- 823
1
vote
0
answers
51
views
What is the best statistical approach to forecast cash flow from run-off debt vintages with a growing balance?
community.
I'm facing a modeling problem for cash flow forecasting and would like to know what the most robust mathematical/statistical approach is to solve it.
The Problem: Debt Recovery Forecasting
...
- 215
1
vote
0
answers
33
views
Need advice on length of context for future prediction
I'm using a trained foundation model to forecast values on a time series. The model works by taking a window of recent data (context) to predict near-future outcomes (horizon).
How can I know the ...
- 11
1
vote
0
answers
18
views
How to use a hierarchical Bayesian model to combine regional and country-level data for TPES projections?
I’m trying to project TPES (Total Primary Energy Supply) by country in Africa up to the year 2100 under different SSP (Shared Socioeconomic Pathways) scenarios, the same framework used in the latest ...
1
vote
1
answer
47
views
Forecasting with VAR models after differencing some time series
i have data from 85 participants who answered 6 items for 82 consecutive days. In other words: I have 6 time series per participant. I already imputed the missing data, so that all time series have ...
- 61
4
votes
1
answer
150
views
Is using contemporaneous components to forecast an aggregate a valid method or a form of data leakage?
I am in the middle of a deep methodological debate regarding a time series forecasting problem and would appreciate the community's expert opinion.
The Context
I am trying to forecast an aggregate ...
- 308
0
votes
0
answers
50
views
Sampling counterfactual posterior to mitigate error autocorrelation in event studies
I have question regarding event studies (pre-event data is observed, an event occurs at $t=e$, then following the treatment is assumed to be in-effect.)
There are multiple approaches to event study ...
- 3,970
0
votes
0
answers
40
views
Forecasting beta distributions
I hope you are doing well. I would appreciate your help with the following questions (listed at the end).
Context
There is a financial aid program that covers tuition fees for university students for ...
- 133
5
votes
4
answers
1k
views
What is difference between nowcasting and forecasting?
Recently I crossed to this Github Repo trying Benchmarking econometric using ML models in nowcasting GDP (see the paper).
Q1: What is difference between nowcasting and forecasting over time data in ...
- 579
1
vote
0
answers
45
views
Dynamic Linear Model: Classical vs Discount Approach
I'm working on a time series forecasting problem and trying to decide between the classical approach and discount approach for Dynamic Linear Models (DLMs).
Anyone here has experience comparing these ...
- 73
4
votes
1
answer
197
views
Can I have some help choosing a very low-sample estimator?
I want to forecast what next semester's finances may look like, regarding my campus job. I get paid bi-weekly, and have eight past data points: ...
- 143
-1
votes
2
answers
191
views
Quantile regression: But which quantiles (conditional on what)?
I have a task of making a quantile regression (5%, 50% and 95%) for tomorrow's power production. However, I am trying to grasp which quantiles we are talking about. Wikipedia (and similar sites) ...
5
votes
1
answer
172
views
Distribution based loss for regression with unbounded data
Currently I am dealing with time-series data conserning the power consumption of machines. Therefore, all target variables range from zero to infinity, technically ($y \in [0, \infty)$). The data ...
- 153
4
votes
1
answer
93
views
