Unanswered Questions
1,417 questions with no upvoted or accepted answers
12
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Empirical Prediction interval for time series forecast based on quantile regression
As Gardner notes "almost all point forecasts are wrong", so prediction intervals (PI) are necessary to quantify uncertainty and help us make informed decisions. There exists theoretical PI, and in ...
- 8,815
8
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1
answer
898
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Forecasting daily visits using ARIMA with external regressors
I have daily visitors data for the last 10 years. I want to do some basic tests like which is the busiest day, which is the busiest month, busiest week etc. I used ...
CommunityBot
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7
votes
0
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730
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Does backcasting work the same way as forecasting?
Context: I have $K$ timeseries over the interval $[0,T]$ and $N$ timeseries over the interval $[S,T]$, and would like to backcast the $N$ timeseries over the interval $[0,S]$.
I am quite new to this ...
- 221
7
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Time Series forecasting with Gaussian Processes
I am trying to forecast various time-series with Gaussian Processes, using the functional approach like in the Mauna Loa example in section 5.4.3 of "Gaussian Processes for Machine Learning". (X = ...
- 91
7
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Irregular Seasonality in time series
I understand seasonality of a time series normally means a cyclic component with constant frequency. For example, the frequency is 24 for daily cyclic trend of hourly data. One of the basic models ...
- 84k
7
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Reorder point with stochastic lead time and demand
I'm trying to determine the optimal reorder point for some products. The reorder point must be greater than the demand during lead time a $\%$ of the times that I should determine, let's say $95\%$.
...
CommunityBot
- 1
7
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0
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6k
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Accuracy of aggregate vs. disaggregate forecasting
I've found a few interesting articles online on this topic, but none which appear to be too cut and dry.
My question is coming up with an accurate predictive forecast based on forecasting individual ...
- 12.4k
7
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392
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Forecasting a complex time series by splitting into subseries
I have finance data that I need to forecast out for 7 years. My data is generally debits and credits, and those are split into a number of sub-series which share common traits (e.g. similar ...
- 1,561
6
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1
answer
550
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Calculating pseudo-$R^2$ for out-of-sample probit model forecasts
I'm trying to replicate parts of:
Estrella, A., & Mishkin, F. S. (1998). Predicting U.S. Recessions: Financial Variables as Leading Indicators. Review of Economics and Statistics, 80(1), 45–61.
...
CommunityBot
- 1
6
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0
answers
2k
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Hierarchical time-series forecasting with complex aggregation constraints
I'm trying to forecast multiple time-series with a hierarchical structure using the hts package by prof. Hyndman. However, the aggregation constraints are not sums ...
CommunityBot
- 1
6
votes
1
answer
378
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Comparing variances of forecast errors
I am forecasting a weekly commodity price series. I use a rolling window for estimating my model, and from each window I make point forecasts for one and two steps ahead.
I want to investigate ...
CommunityBot
- 1
6
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0
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698
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is it sensible to use monte carlo to predict sum of time-series over an interval?
I have created a model that forecasts out a time series at the daily level along with prediction intervals two months into the future. There is little to no auto-correlation in the time series so I ...
5
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0
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377
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Is there a theoretical reason why simple models perform better than complex models on time series forecasting tasks?
Empirically, simple forecasting methods such as damped trend exponential smoothing, STL, or even random walks typically outperform more complex models such as higher order ARIMA models or ML based ...
- 13.1k
5
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answers
1k
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Does there exist a variant of ARIMA allowing for weighted samples?
I have a univariate time series exhibiting strong periodicity that I want to forecast, and I plan to use ARIMA. However due to specifics of the prediction task that I'm interested in performing, some ...
- 2,059
5
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Gaussian process regression and optimizing an RBF kernel for forecasting?
I'm using gaussian process regression with an RBF kernel to forecast a time series. I'm using GaussianProcessRegression in ...
- 1,067