Questions tagged [time-series]
Time series are data observed over time (either in continuous time or at discrete time periods).
9,086 questions
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Regression with non-stationary data
I am doing time series regression (the form I prefer is what SAS calls regression with AR error a form of GLS that runs OLS on the residuals and that has various names in the literature). The problem ...
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Testing for annual patterns of sex ratio without time series analysis
I have data on the number of males and females from a single population, sampled approximately monthly for about five years. The hypotheses to test are:
The sex ratio is skewed
There is a trend ...
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13 views
How to explain the decision rationale of time series data classification task using deep learning model
Is there a way to explain which part of the time series data the model is looking at in task that classifying time series data (e.g. video) by deep learning model?
When deep learning model using RNN ...
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9 views
Parameters Grid Search for Keras LSTM on Time Series
How do you do grid search for Keras LSTM on time series? I have seen various possible solutions, some recommend to do it manually with for loops, some say to use scikit-learn GridSearchCV. Feedback ...
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Which model can I use in my regression analysis if I have time series data?
This is my data set I have collected for a 10 year period. My dependent variable is Gini Coefficient and the rest are my independent variables.
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Time-series forecasting of weakly correlated, univariate series
Given an event that happens with a probability of $\lambda_1$, and another event happens with a probability of $\lambda_2$, what is the probability that they both occur?
I have a dataset of ...
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1answer
36 views
Time series ARIMA question
I am new to time series, and here i have a question about ARIMA- determine the order of MA and AR.
In one post i learnt that usually we use the ACF and PACF plot to determine whether we should use a ...
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17 views
non-stationary time series for VAR model forecasting
I'm working with a VAR model to do forecast involving two non-stationary time series (quarterly frequency). The literature indicates to verify if there is cointegration and, otherwise, to use the ...
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14 views
Using Weekly Google Trends Data in Stata [on hold]
Google Trends provides weekly Google search data from Sunday to Saturday. I would like to perform a time series analysis of Google Trends data in Stata but am having difficulty getting Stata to ...
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28 views
How do you choose an appropriate time series regression model?
I am working on a research proposal where I want to test the effect of different macroeconomic variables (i.e. government spending, FDI, trade openness, international GDP growth, etc.) on the GDP ...
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9 views
Are VAE used for missing data imputation in multivariate time series? If not, what is used?
Multivariate time series are, to the best of my understanding, one of the few cases where Deep Learning still hasn't had its AlexNet moment. I'm especially interested to the case where most of the ...
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36 views
Scalability of Tsoutlier
I am currently using TSO() in R to find the anomalies. I am doing this for last 3 years daily data. I am getting the output as well with list of anomalies.
If i need to repeat on a daily basis with ...
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What method or algorithm is used for computing Power Curve in cycling power data analysis?
Many cycling analytics apps, for example, Strava, TrainingPeaks or GoldenCheetah are offering the Power curve chart, computed from the cycling power time series data. I'm familiar with the curve ...
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22 views
Using non-stationary time series in cross-correlation analysis
I have modelled organism dynamics and abiotic factors time series in order to understand their seasonal oscillation and trend over time. Now I want to identify if there are any correlation between ...
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19 views
How to interpret ARIMA (1,0,0) model? [on hold]
I'm doing time series for my masters thesis, thus I need to interpret som ARIMA models. The data consist of number of recordings per night throughout the summer.
I think I'm done with my coding now, ...
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7 views
Software that finds correlations between loosely dependent time-series?
I'm not sure if this is the right kind of question for this site, so please let me know :)
I'm looking for a time series data analysis platform, so I can take a collection of time series at 15-...
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1answer
24 views
How does facebook prophet handels missing data?
Prophet's paper (forecasting at scale by SJ Taylor - 2017) says the following on missing data:
"Unlike ARIMA models, the measurments do not need to be regularly spaced, and we do not need to ...
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38 views
Tsoutliers takes very long to execute [on hold]
I have 3 years of daily data (Continous variable) ex: exit rate from a website. I am trying to do anomaly detection using tso function. But R studio is taking a very long time... More than 30 - 45 ...
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Forecasting Demand for Multiple Products with Adjusted Sales Quantities and Different Dates
I am working on a task forecasting demand for 86 products that are sold to 6 customers. 81 products are customer-specific, i.e., they are sold to only one specific customer. 5 products are combined ...
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1answer
41 views
sklearn Support Vector Regression - test data prediction is constant
I am just getting into learning some basic machine learning for a project at university and I am having a little trouble with SVR on sklearn.
When training a model I can change the epsilon value and ...
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1answer
17 views
Normalizing Time Series Records of Different Time Lengths
I have several million records, some of which have data points for few time points (>=3 time points) and others have data for hundreds of time points. How do I normalize data of different time lengths ...
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1answer
30 views
Finding the most suitable measure of location and dispersion for price time series data [on hold]
I have a long list of data of the price of oil over the last five years. Which measures of location and dispersion is advisable for me to use to present the data. The data were given like this:
<...
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1answer
37 views
Does SARIMA(3,1,18)(8,1,3) exist?
When I entered the above model in minitab to forecast, it said, 18 is not acceptable, and that value should be less than or equal to 5. I wonder whether it's a limitation of minitab, or this model is ...
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1answer
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Interpretation of spectral entropy of a timeseries
The tsfeatures package for R has an entropy() function. The vignette for the package describes it as:
The spectral entropy is ...
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17 views
Generating 100 independent samples in R [on hold]
I have the following problem, and I am completely lost on how to get started. I am a completely new to R, so I am not sure how to generate the required data. Any ideas?
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1answer
36 views
Forecasting in R - really short time-series
Complete noob on forecasting and time-series here.
I'm doing my PhD and my group did previous research on the prevalence of the disease we're studying. We only have prevalence data of 5 years and ...
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1answer
21 views
Predicting items based on time and weather
I've got a data-set with items bought, the time it was bought (I can add the weather of the location at that time of the day). I would like a simple "prediction" model based on time and weather.
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Error in makeARIMA : maximum supported lag is 350 [on hold]
I have 4 years of temperature data with datapoint per each day. I am unable to use the lag 365 in sarima function because maximum supported lag is 350. Is there any alternative to use lag 365??
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The Importance of Initial Conditions in Autoregressive Modeling
I am developing an algorithm to classify time series by using autoregressive modeling. I have used the following two alternative methods, after fitting an AR(p) model to time series:
Method 1: ...
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9 views
Is it possible to make LSTM model with 4dimension shape?
Hellow, wizards. I have time series data including sevaral days.
I try to predict a grade of tomorrow, which is range from 0 to 100. And I assume that this grade depends on 3 time-series independent ...
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1answer
19 views
AR(1) Finding $\gamma_l$
I have $\gamma_l = Cov(r_t, r_{t-l})$ as a definition in my notes and now I need to find $gamma_l$ for a series $r_t- m = p(r_{t-1} - m) + a_t$ where $r_t$ is a linear time series with expected value $...
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30 views
Ridge Regression and Unit Root Test [on hold]
Is it necessary to check whether the data contains unit roots before Ridge Regression estimation in time series?
We have to check Gauss-Markov assumptions in OLS estimation. Is Gauss-Markov ...
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18 views
Arima with multiple autocorrelation coefficients [closed]
I am new to time series analysis. I want to know that if it is possible to build an ARIMA Model with multiple p-values taken at once.
I mean, if time series is related to multiple time lags, in that ...
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1answer
19 views
Is there a way to select a correct time period for GLM modelling? [closed]
I am working on demand models (specifically cancellations, renewals for finacial products) and I have access to about 5 years of data. I will be using a GLM for the model and need to select the time ...
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1answer
14 views
Higher value of strides in conv1d
I am using Conv1d for time-series data and I have create a model as follows,
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1answer
19 views
Time series cross validation
Reading through the scikit learn documentation on time series cross validation (https://scikit-learn.org/stable/modules/cross_validation.html#cross-validation-of-...
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26 views
Lower ARIMA accuracy with BOX-COX
I'm using ARIMA model for time series forecast. My data has increasing variance and I applied a BOX-COX transformation to stabilise it. Here are charts:
After I run my app it turned out that ARIMA ...
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2answers
80 views
Is $(1-L)Y_t=\epsilon_t \to Y_t=(1-L)^{-1} \epsilon_t$ mathematically correct?
Consider an AR(1) model with coefficient $\rho =1$, i.e. a random walk, $Y_t=Y_{t-1}+\epsilon_t$. We usually say that since the AR polynomial has a unit root, it cannot be inverted and therefore the ...
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32 views
Analysis of Time Series data [closed]
The below graph is a scatterplot of daily stock price. My aim is to predict future stock price of the company.
From the scatterplot it seems that it is a multiplicative model, so I tried to "...
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24 views
Can someone tell suggest what this series might be? [closed]
I have this weird ACF and PACF plots and would like to know proper model/ plausible decomposition?
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9 views
Stationarity of ADL(p, q) with heteroskedasticity
Suppose I have the model
$$y_t = \alpha_0 + \alpha_1 y_{t-1} + ... + \alpha_p y_{t-p} + \beta_0 x_t + ... + \beta_q x_{t-q} + \epsilon_t,$$ where $\{x_t\}$ is a stationary process and $\epsilon_t$ has ...
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11 views
Coding a BEKK mutlivaraite GARCH model
I have the code, but I am struggling to determine which specific BEKK model it is for...
Any advice would be appreciated,
...
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0answers
19 views
Hierarchical time series using DLM
I am developing a forecasting solution using R's dlm package and it is proving to be very useful for most of our requirements.
However, I am also keen on sharing information among different time ...
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18 views
How to implement a SARIMA-GARCH model?
I was reading "Prediction of daily peak electricity demand in South Africa using
volatility forecasting models" by C. Sigauke and D. Chikobvu about electricity demand forecasting and I'm interested in ...
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8 views
Feeding Embedding Vectors With Time Series Data to LSTM [closed]
I have daily sale data of some retail products on a three year span and I want to build a model that can predict future sales for all of these products. While looking for a way to forecast multiple ...
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0answers
6 views
What is the best calculation method to account for individual change, volatility, observation windows and time decays in time series data? ARIMA, ETS?
I am looking at applying a theoretical best calculation method to some particular time series (ts) data. Ideally the calculation method would encompass relative change in individual ts, volatility of ...
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9 views
How to use seasonal features in time series regression with models such as xgboost?
I have a hard time understanding how one can create seasonal indices such as a yearly mean or (x - yearly mean(x)) and use them as predictors for monthly n horizon forecast.
For example:
I want to ...
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1answer
27 views
Anomaly detection with complex seasonality
I am working on a anomaly detection for a batches of daily time series (non-hierarchical) that exhibit both yearly and weekly seasonality. I tested a few algorithms and it appears that tbats() from ...
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1answer
17 views
Existence of weakly stationary process for given mean and covariance
I know that if a process is weakly stationary, the mean of the process will be time-independent and the covariance will be a function of the time difference.
My question: if I have a time-...
