Unanswered Questions
3,066 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 ...
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8
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What is the intuition for testing seasonal difference with OCSB test and its correct application?
I have daily time series data of a shop's revenue. Now I would like to test for seasonal differencing with the OCSB test originally intrduced in (Osborn et al. (1988): Seasonality and the Order of ...
- 103
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
answers
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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0
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2k
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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
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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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0
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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
7
votes
1
answer
5k
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Improve precision/recall for class imbalance?
Trying to get better precision/recall for both classes ... any tips?
I have heterogeneous features [a few num vars, a few cat vars, and 2 text vars]
Target is a binary classification w/ class ...
CommunityBot
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6
votes
0
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138
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Time series predictions with LSTM
I have collection of TEC data.My data sample for example the day1,day2,day3,day4.
Case1:
I have the following task to do: Training by the consecutive 3 days to predict the each 4th day. Each day data ...
- 33
6
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0
answers
140
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Given a multiple-choice survey, test the hypothesis that choice i is more common in the population than choice j
I have a survey with m possible choices, only one answer allowed for respondent. Let $n$ be the sample size, and $\tilde{p}_k=\frac{n_k}{n}$, $k=1,\dots m$, the observed frequencies for each choice. ...
- 18.5k
6
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0
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97
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Posthoc pairwise test on the output of a linear mixed-model (MATLAB or R/Python)
I have observations from three groups of participants (A, B, C), that each represent ratings on three different measures (measure 1, 2, and 3). I would like to know if it is the case that, regardless ...
- 2,352
6
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Why SVM with gamma='scale' for RBF kernel works so well?
The intuitive explanation for the gamma parameter of the RBF kernel in SVMs is the following:
Intuitively, the gamma parameter ...
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6
votes
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.
...
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