Questions tagged [time-series]
Time series are data observed over time (either in continuous time or at discrete time periods).
14,130
questions
0
votes
1
answer
23
views
in-sample and out of sample forecasting plot look very different
why the in-sample looks very different from the out-of-sample? Is the in-sample overfitting? Horizon is 12, using pycaret time series function.
- 121
0
votes
0
answers
20
views
Using Bayesian statistics in time series forecasting
I would like to forecast demand count time series of taxi fleets at different locations on the map at different points in time. I.e. multivariate demand Time series forecasting.
Given hierarchinal ...
- 244
0
votes
0
answers
9
views
Eventual Forecast Function [closed]
(1 - 0.43B)(1 - B)Zt = at
How do I calculate the eventual forecast function for an ARIMA(1,1,0) model? My textbook does not explain for this specific model...
0
votes
0
answers
11
views
Comparing two countries using time series data
I'm considering using time series data to compare Spain's and China's economic performance during various years of economic growth. However, I'm wondering if it's valid to compare them when they ...
0
votes
0
answers
25
views
Resources for Probabilstic forecasting
I was planning on learning probabilistic forecasting and im completely lost. Suggest some online resources. I have started with Probabilistic Forecasting and Bayesian Data Assimilation but its a bit ...
0
votes
0
answers
56
views
Design of experiment in multiple regression
Suppose we have the following model of our environment:
$\hat{y}_t = e^{dayofweekeffect} * x_{1, t}^{\beta_0} * x_{2, t}^{\beta_1}$
which we can linearize into: $log(\hat{y}_t)= dayofweekeffect + \...
- 1
1
vote
0
answers
26
views
Prediction based on new data in the tsDyn package [closed]
I decided to use the tsDyn package to build the model and precision the values. The argument for this package (I previously worked with urca, vars) was the ability to make predictions based on new ...
- 111
0
votes
0
answers
9
views
Prediction when Target's lag values are part of Predictors
I'm using LGBM for regression, where the Target column's lagged values (7 columns for each lag day) are also used as predictors when training the model. Absence of the 7Day lag values severely ...
- 25
-1
votes
0
answers
28
views
Due to limited information How can I restructure my model to capture this relationship? [duplicate]
I created a model for prediction. The target data has a total of 4 classes (0-3), which makes my model completely ineffective. Due to limited information How can I restructure my model to capture this ...
- 1
2
votes
1
answer
80
views
E-commerce - Does higher delivery time lead to lower sales?
Question
I have a practical problem and am seeking guidance on how to use statistical methods to solve it.
I have an online store. The products in the online store have varying availability:
24 hours ...
- 121
1
vote
0
answers
22
views
How come the deterministic part of Wold decomposition does not violate stationarity?
Wold's representation theorem states that every covariance-stationary time series $\{Y_t\}$ can be written as the sum of two time series, one deterministic and one stochastic:
$$
Y_t=\sum_{j=0}^\infty ...
- 63.6k
0
votes
0
answers
20
views
Notation for an ordered pair of stochastic processes
There are two stochastic processes, $\{ Y_{1,t} \}$ and $\{ Y_{2,t}\}$. If I take them as an ordered pair, what notation do I use:
$\{(Y_{1,t},Y_{2,t})\}$,
$\{(Y_1,Y_2)_t\}$,
$(\{Y_{1,t}\},\{Y_{2,t}\}...
- 63.6k
0
votes
0
answers
31
views
Preventing Data Leakage in Time Series Forecasting with Feature Engineering
In a previous question (linked here), I sought guidance on forecasting thousands of time series. Based on the suggestion to treat it as a regression problem, I used the LightGBM model with extensive ...
- 13
0
votes
0
answers
7
views
How to handle recent variable change resulting in level-switch in time series modeling?
I developed a script to run time series models on people data, and I re-run the Arima model fitting/forecast reconciliation algorithm monthly as new data comes in. I use the grouped/hierarchical time ...
1
vote
1
answer
23
views
Bad performance of ARIMA model on online buzz data, Any suggestions?
I was wondering if the ARIMA model is constrained to predict online buzz data (time series data).
What I want to do: Use the past round 30 months data to predict next month; and I use Python
Here are ...
- 13
0
votes
0
answers
34
views
Can I test for significant difference between samples of a single time series?
I am trying to find a statistically sound way of analyzing my time series data. The data and questions are pretty simple:
Experiment setup
I have an estimate of the rate at which a crustacean consumed ...
1
vote
0
answers
9
views
Include variance change at point in ARIMA model estimation in R
I have a series which I am trying to model through ARIMA approach. However, when checking the residuals, there appears to be a change in variance at a specific point. This is, given the residuals $e_t$...
- 330
0
votes
0
answers
17
views
Granger causality does not imply a pair of integrated time series are cointegrated: an example
If a pair of integrated time series $\{X_t\}$ and $\{Y_t\}$ are cointegrated, at least one of them must Granger-cause the other. Is the converse also true? I guess not, but I am struggling to come up ...
- 56
0
votes
0
answers
15
views
How to construct forecast confidence interval from the historical RMSE?
I'm reading a FED paper on forecast uncertainty estimation. Here's the link
One of their methods to estimate forecast interval is illustrated in the following figure
According to the description: &...
- 699
0
votes
0
answers
26
views
How to interpret those ACF & PACF?
I have some problems when analyzing my time series dataset.
Basically, the dataset is about the daily sales volume of an FMCG company (they work from Monday to Saturday with Sunday being a day off, so ...
- 1
0
votes
0
answers
17
views
Is it possible to specify correlation structure for mixed models in Julia? [closed]
Is there an equivalent approach to the following mixed model, growth curve analysis in Julia:
...
- 655
0
votes
1
answer
118
views
Multiple correlations across subjects
I have a bunch of data where I am recording two variables across time for many subjects: velocity of the right hand, and intensity of the speech.
For each of my 20 subjects, I have ~30 recordings of ~...
- 1
1
vote
0
answers
44
views
Improve HMM state estimation in latest data
I have a time-series dataset that is poisson-distributed, where each day I get a new additional datapoint. If I input all the data into a HMM (I am using code I found from hmmlearn in python) it does ...
- 43
1
vote
0
answers
37
views
Adding a New Feature
My question is pretty straightforward and the task behind is related to binary classification. To add a new feature, do i first do train_test_split then add a new ...
- 11
0
votes
0
answers
24
views
Optimization problem involving VAR
I'm looking to solve, from the paper https://arxiv.org/pdf/2210.02176.pdf,
$$\min_{g\in VAR(p)} \sum_{z\in \mathcal{Z}} (f( h_{x}(z))-g(z))^2\pi_{x}(z)$$
where $\mathcal{Z}\in \\{0,1\\}^{N\times W}$ ...
- 507
0
votes
0
answers
19
views
Moment-generating function of an ARMA process
If $X_t$ is an ARMA(p,q) process is it possible to derive its moment-generating function?
- 1
0
votes
0
answers
20
views
where's a good reference and community for help with getting started on Bayesian time series analysis?
I am trying to learn the basics of Bayesian time series analysis, but am having trouble finding some up-to-date basic examples and a discussion forum where I might be able to get some guidance. (...
- 131
0
votes
1
answer
33
views
Can I use the residuals of a time series decomposition to estimate the effect of a covariate?
Context
I work for a company that has an e-commerce website. Regularly we make specific campaigns in order to sell more. For example: We can make a campaign for fathers day, black Friday, crazy August,...
0
votes
0
answers
19
views
Statistical procedure to remove a time series which is an "outlier" in a set of replicated time series
This data are from measuring optical density in a bacterial growth experiment. These correspond to 4 time series which are biological replicates of exactly the same treatment (with the label 0_4)
The ...
0
votes
0
answers
34
views
Multiple comparison problems for Unit Root testing
Lets say I have a multivariate time series and I will run unit root tests for each variable to figure out if the variable is stationary and how many differencing are necessary to make it stationary.
...
- 1
0
votes
0
answers
7
views
Metric for run-to-run consistency of time series data
If I run $n$ samples of a physical experiment, I expect to see roughly similar time vs. position plots but with slight variations run-to-run. What are good statistical metrics to quantify the ...
2
votes
1
answer
32
views
Statistical Method for Accurately Detecting Seasonality in Monthly Sales Data
I have a dataset containing monthly sales data for different product categories spanning five years (60 months of data). I am using a Python process to calculate the seasonality for each category, ...
0
votes
0
answers
33
views
How to predict more than one future values in ARMA model
I want some help with predicting more than one future values in ARMA. I saw that the similar question has been asked here. But it is only helpful for predicting one future value.
For estimation of the ...
2
votes
1
answer
36
views
Forecasts fail for new period
I am working with prophet library in python where I do some forecasts. While I split to train and test to check, it shows very good performance, but when I forecast for the actual future period it ...
- 21
0
votes
1
answer
20
views
How to obtain seasonally-adjusted time series data using STL in Python
On the section "STL decomposition" in the 2nd edition of Forecasting: Principles and Practice, it says that the seasadj() function can be used to compute ...
- 77
0
votes
0
answers
6
views
How to dectect sudden change in signal frequency? (analysis of EEG signals)
I am trying to analyze data from EEG electrodes to understand how brain activity changes in different coginitive states (for simplicity, assume that there are only 2 states: baseline (A) and chanelled ...
- 211
0
votes
0
answers
18
views
Simulation of a time series using the unconditional moments
$y_{t}$ follows a covariance stationary AR(1) process
$ y_t = \phi y_{t-1} + \varepsilon_t \hspace{1cm} \varepsilon \sim \mathcal{N}(0,\sigma^2) $
I want to simulate a time series $y_{1:T}$. Can I use ...
- 189
0
votes
0
answers
26
views
What should we consider when visually evaluating non-stationary data before making assertions?
I often see charts displaying multiple time series plotted together and they are often accompanied by explanations relating one series to the other. For example, in the below chart, one might say less ...
0
votes
0
answers
6
views
Stationarity and Chow-Lin disaggregation
My goal is to have higher frequency data (quarterly) for the GDP of my region (yearly data) through quarterly auxiliary data. Therefore my goal is to perform a Chow-Lin regression using the package <...
- 113
0
votes
0
answers
8
views
Question on Cochrane–Orcutt estimation. Can I simply use inverse of the lag operator?
I came across the Cochrane–Orcutt estimation, which is concerned with regression-type estimates in cases where errors are AR(1) correlated. My question is whether I can formally apply the inverse of ...
- 426
0
votes
0
answers
18
views
How to vectorize a recursive relation (AR in Bootstrapping)? Possible?
I´m working towards the resolution of all questions in Efron & Tibshirani 1993. The Introduction to the Bootstrap. I got stuck in question 8.6.
It is related to the bootstrap of an AR process, ...
- 71
0
votes
0
answers
62
views
Testing if some process has missing data
I am studying a time process, consisting in events occuring at some dates, one after the other (typically one event every 1-2 days, sometimes several in a day, with data covering circa 20 years). I ...
- 131
0
votes
0
answers
16
views
Matching time series plot with ACF plots
We have to match time series plot in the 1st row with the ACF plots in the second row. The solution for the same is given below. However , It would helpful if someone could explain the solution.
1
vote
1
answer
39
views
Monthly data with seasonality: is linear regression appropriate?
I have the following situation: there is data for six years, per month. In a year you can see variation per month, since the data is influenced by the seasons. Also, there is an upward trend over the ...
- 11
0
votes
1
answer
18
views
Is the R2 statistic affected by normalizing your timeseries?
I have been trying on comparing to time series, one predicted and one measured. One of the first and most simplistic statistics that can help is R2. I have no issues calculating R2 but my supervisor ...
0
votes
1
answer
26
views
High Level Time Series Forecasting Question given a set of unknown data sets
I have this question regarding 4 data sets where one of the data sets is missing half of the data. The data is relatively correlated, but not perfectly. How may we construct a model to produce the ...
0
votes
1
answer
49
views
Can this be considered overfitting?
I have been trying to use the LSTM model for a monthly time series with a length of 404 (384 for training and 20 for test). I created 4 pairs of training/validation sets, trained different models, and ...
0
votes
1
answer
21
views
Comparison of time series: Cluster behaviors / detect anomalies
I am studying a dataset of time series for different users. The dataset contains records of actions (or registrations) of the users over time. I have data of a whole week for about 80,000 users.
...
- 1
0
votes
1
answer
89
views
Why use sliding window input features in sequence modeling?
I was reading through the DNABERT paper and found that their input features were k-mers. This is equivalent to using rolling/sliding window features in the other common family of sequential problem, ...
- 62
2
votes
0
answers
203
views
Simulate time series with periodic spikes
I have multiple time series representing a process that operates in batches. It consists of many small intervals interleaved by periodic long intervals (spikes) at the offset of each batch. The period ...
- 2,348