Questions tagged [time-series]

Time series are data observed over time (either in continuous time or at discrete time periods).

Filter by
Sorted by
Tagged with
0 votes
0 answers
13 views

How do I handle basic time series prediction?

I have data like: may 2019 value=74 cost centre=c1 and I want it to predict values for cost centres. The data is monthly and I only have a few years worth (max 48 ...
user avatar
  • 133
1 vote
0 answers
8 views

Using weather forecasts as exogenous data for timeseries forecasting

I'm using Facebook Prophet as a forecasting model and I want to use weather data (temp for example) as additional regressor (exogenous data or external variable). Additional regressors are integrated ...
user avatar
  • 123
0 votes
0 answers
5 views

How to convert multiple rows into single rows in Python for prediction for next t days?

I have time-series data. I have taken the dataset from Kaggle [https://www.kaggle.com/code/kp4920/s-p-500-stock-data-time-series-analysis/comments]. So, how can I bring multiple rows into single rows ...
user avatar
1 vote
1 answer
51 views

Variations of difference-in-difference method

I have data from a group of patients and for each patient I have two time series A and B (continuous quantity) sampled on a weekly basis. My hypothesis is that quantity B has a 1-week lagged effect on ...
user avatar
0 votes
0 answers
16 views

How does the dynamic regression component from TBATS differ from the one in SARIMAX?

Both TBATS and SARIMAX support the modeling of long-term seasonality by using dynamic regression. Dynamic regression in this case involves the use of sin and cos terms to model seasonal components. In ...
user avatar
  • 2,032
1 vote
0 answers
22 views

Seasonal and trend adjustment for irregularly spaced time series

I know of different methods that exist to remove seasonality and trend in the data to make it stationary. However, that exists only for regular time series; that is, a series that follows a fixed ...
user avatar
0 votes
0 answers
21 views

Difference between cross validation vs model accuracy measures

I have a time series ARIMA model and I want to validate the accuracy my prediction. But I dont understand the difference of using cross validation vs model accuracy measures such as MAPE, MAE, MSE and ...
user avatar
  • 1
0 votes
0 answers
33 views

Time series - ARIMA Model gives bad result of prediction

I don't understand why I get poor prediction results with ARIMA Model Here is my program and my results: for the dataset I am using a file (which represents CPU traces of one VM)that contains 288 ...
user avatar
2 votes
0 answers
18 views

Identify predictors for a symptom in a time series

I have a dataset of time series. The analogy for each series is a medical history (2-3 years) of a patient visiting a clinic. It consists of dates and symptoms per visit: There are few thousands of ...
user avatar
  • 21
0 votes
0 answers
9 views

States in RNN: what if they are measured

A simple RNN will take the output and feed it back to a state variable. The next output is then the function of input and state. Now imagine I want to use the "state" variable in RNN as an ...
user avatar
0 votes
0 answers
30 views

Seasonality component and stationarity of a time series

I am not able to understand the seasonality pattern in the below plot. For me, the series has obvious seasonality (except for 2014 year) where levels tend to increase in the early months of the year ...
user avatar
0 votes
1 answer
20 views

Time series model in production - Re-train on the fly as as batch process?

Let's say I've a time series of phone calls per day over the last three years. I could train a model using exponential smoothing (e.g. HoltWinters) for predicting the future amount of phone calls per ...
user avatar
  • 101
0 votes
1 answer
18 views

Comparing intervention/control group

I am planning to conduct a study which is based on an RCT design. I am intending to conduct an intervention. During this intervention, participants and control group enter some medical data on daily ...
user avatar
  • 3
0 votes
1 answer
20 views

Missing Prediction Intervals by R package autoTS

I'm using autoTS R package to fit automatic time series estimation and prediction to a very very large number of time series. One of the outputs of the prediction function (my.predictions()) is a 95% ...
user avatar
  • 3
0 votes
0 answers
18 views

R package for order selection of a vector ARIMA(p,d,q) for multivariate time series

I'm currently working on a project that requires dealing with multivariate time series. What I would like to fit to my dataset is a VARIMA(p,d,q) . I'd like to proceed using the Box-Jenkins procedure, ...
user avatar
0 votes
0 answers
18 views

How to derive variance of an AR(1) model? [closed]

I am trying to derive the variance of $Y_t$ and $X_t$. Please help.
user avatar
  • 1
1 vote
0 answers
28 views

Do the variables used in computing the mean and variance have to be i.i.d.?

For example if you have a theoretical server that processes incoming requests where in this case there are so many requests that the callback delays depend upon each other, can you just take the ...
user avatar
  • 111
0 votes
0 answers
7 views

Can you generate correlated ARMA time series with different lag orders?

Is it possible to generate correlated ARMA time series when the ARMA models are different? For example, can you generate two time series which are correlated when one is an AR(5) model and one is an ...
user avatar
1 vote
1 answer
16 views

Interrupted Time Series Design with multiple groups

More of a conceptual question The standard ITS design is pretty simple, regress: Y ~ Time + Treatment_Dummy + Time_Since_Treatment However, what if the scenario was ...
user avatar
0 votes
0 answers
20 views

Is stationarity of variables neccessary condition for Bayesian VAR?

I am trying to run a BVAR on 5 variables. Four out of five are non-stationary. So shall I do the first difference of the non-stationarity variables or take them in level for running the BVAR? And what ...
user avatar
0 votes
0 answers
31 views

How to calculate harmonic equations from a complex wave

I’m working through an online example that explains spectral analysis in R. Let’s say you have a complex wave: ...
user avatar
  • 23
1 vote
0 answers
7 views

Structural or sensitivity analysis of multivariate time series with multiple subjects

Sorry if this isn't explained in the best way. I have very basic knowledge of time series analysis so my question may sound very simplistic or might be missing the big picture of this type of analysis....
user avatar
0 votes
0 answers
11 views

Time series data with seasonality using model VAR and VARMA [duplicate]

I have a time series with seasonal economic data, and other time series to see if this variable help predict my time series, but the VAR model is not a model for seasonality. What options do I have ...
user avatar
1 vote
1 answer
22 views

Concatenation or separate channels for a CNN

let's say I am classifying time series data from multiple channels in a biomedical setup (e.g. 12 lead ECG). I have been reading this paper on a CNN-based (ResNet) architecture for assesing the ...
user avatar
  • 111
0 votes
0 answers
7 views

Are stacked meta models for time series forecasting still considered forecasters?

I am working on building a meta model that is based on the principle of stacked generalisation (1). In a nutshell, this method works by using building a meta model based on the predictions of various ...
user avatar
1 vote
0 answers
9 views

Efficient storage of functional data

I have access to a sample (size $N$) of functional data. Each observation corresponds to $C$ functions. Each function $f_{n,c}$ is represented by $T_n$ points for $1\geq n \geq N, 1\geq c \geq C$. All ...
user avatar
  • 2,049
0 votes
0 answers
12 views

Difference K-fold versus Blocked Cross-Validation?

In the paper "Evaluating time series forecasting models: an empirical study on performance estimation methods" by Cerqueira et al (2020), they mention k-fold cross-validation. Which they ...
user avatar
0 votes
0 answers
26 views

Understanding types of LSTM and their use cases

I'm currently considering to use RNN/LSTM for a predictive modelling project that involves time-variant points. From looking at the following types of LSTM/RNN (in the picture below), I want to try ...
user avatar
0 votes
0 answers
21 views

ACF and PACF Plot

I am a first year stat student. We are tasked to create a SARIMA model from trial and error using ACF and PACF plot. Now here is my generated plot: Now I am trying to understand the plot but I don't ...
user avatar
  • 1
2 votes
0 answers
23 views

What is the difference between regression and state-space models?

I would like to know the differences between a regression model with autocorrelated errors and state space models (time series). When should each be used? According to this lecture, regression (linear ...
user avatar
0 votes
0 answers
17 views

Arima model always predicts the same value in python implementation, R's Auto Arima however gives me a well function model. How to replicate?

I have a series that looks like . (https://gyazo.com/8a460fed032c8989b93cf26d8820e431) It shows very strong auto correlation ![AC] (https://gyazo.com/4acd9b9bd32c70509bde1b8b874d6e33). I have ...
user avatar
-3 votes
0 answers
132 views
+50

Alternatives to linear model regression

Let's say I have a univariate linear regression model LMR in which ...
user avatar
0 votes
0 answers
21 views

Practical correlation metric for a large number of vectors

I am dealing with a timeseries consisting of input flow sampled every 5 minutes over 441 days. My aim is to find any possible correlation from data coming from: The same day of the week The same ...
user avatar
  • 11
0 votes
0 answers
19 views

Does the Discrete Fourier Transform have a factor of $n^{-1}$ or $n^{-1/2}$? [closed]

While studying, I have encountered two formulations of the Discrete Fourier Transform, and I am not sure whether the choice of having a factor of $n^{-1}$ or $n^{-1/2}$ in the DFT is arbitrary. The ...
user avatar
0 votes
0 answers
17 views

Modified Structural Break Test

Consider a simple AR(1) model $$y_t=c+\lambda y_{t-1}+\epsilon_t$$ For example using the so called Andrews supremum statistic, I can test for a single structural break in $\lambda$ at an unspecified ...
user avatar
  • 218
0 votes
1 answer
28 views

In a time series $x_t, x_{t-1},...,$, why is $E[x_t|x_t, x_{t-1},...]= x_t$?

Sorry if obvious but in a time series $x_t, x_{t-1},...,$, why is $E[x_t|x_t, x_{t-1},...]= x_t$? I don't really get what the random variable $x_t|x_t, x_{t-1},...$ represents? What I find ...
user avatar
0 votes
0 answers
16 views

statsmodels.adfuller weird behaviour of usedlag value

I'm learning about time-series analysis and have two series on which I'm performing an Augmented Dickey-Fuller test in order to check for stationarity. I'm trying to understand why I get very ...
user avatar
0 votes
1 answer
28 views

How to select a time series model based on this ACF?

I think that I am missing some concepts because I am not able to model adequately this series. It is a times series over 12 years. I tried with multiple AR and MA models, nevertheless, I can't model ...
user avatar
  • 3
0 votes
1 answer
20 views

Conflicting ACF/PACF after first-difference

I have yearly data. When I do a Dickey-Fuller test it gives me insignificant results, indicating that the series are non-stationary. After differencing them the DFT tells me they are now significant ...
user avatar
  • 3
0 votes
0 answers
31 views

How can I adjust cumulative entropy of moose observations?

I have downloaded the dates of every moose (Alces alces) observation worldwide on iNaturalist. This amounts to about $2 \cdot 10^4$ observations at present. I excluded one observation that was either ...
user avatar
  • 3,437
1 vote
0 answers
11 views

Estimation of standard error in observables generated from time series data

Imagine that I have time series data which are time-correlated, non-scalar, and of unknown, but identical distribution From this time series I have a function that takes an subset of X as input to ...
user avatar
1 vote
0 answers
16 views

Slowly decaying ACF plot = indicative of trend or AR(1) process?

I am required to interpret a suitable ARIMA model for the above ACF and PACF plot. My first instinct from the slowly decaying ACF plot and the sharp drop after lag 1 of the PACF tells me this is an AR(...
user avatar
  • 21
2 votes
0 answers
19 views

When do ARMA models fail?

I have just started learning about Autoregressive–moving-average model (ARMA). On the Wiki page, it has been mentioned that: ARMA is appropriate when a system is a function of a series of unobserved ...
user avatar
0 votes
0 answers
17 views

Statistical test for forecast performance over multiple runs

Lets say I have a time series, create a training and test set, and I want to compare the predictive accuracy of two models, by measuring e.g. the mean absolute error (MAE) over the test set. I know ...
user avatar
0 votes
0 answers
19 views

How to forecast sales for entire current month taking into account sales from half of month?

Good afternoon! I want to forecast sales for current month. Since I already know sales for two weeks of current month, I want to incorporate this information into forecast for the whole current month, ...
user avatar
  • 93
0 votes
0 answers
13 views

Over forecasting when using historical data during the pandemic period?

I am new to the forecasting domain. I am dealing with a forecasting task where we had a very high abnormal demand for our products during the pandemic. However, in recent months, the demand trend is ...
user avatar
  • 101
1 vote
1 answer
27 views

Inclusion of year and seasons as variable for regression with non-stationary response?

The common knowledge is that OLS only makes sense if both the response and explanatory variables are stationary (ignoring exceptions like cointegration), as otherwise, there could be effects of ...
user avatar
  • 101
0 votes
0 answers
23 views

how to measure the effect of a recurring event?

I have multiple cities with data on theatre visitors and an event as the mentioning of the theatre in the local news. I want to estimate whether the event of a mentioning lead to more visitors for the ...
user avatar
1 vote
0 answers
24 views

Why does my ARIMA predictions on monthly data form a straight line?

For short detail, the goal was to forecast using 51 monthly observations of KPI of project implementations which I aggregated by sum from 463 observations from about 4 years of data (May 2017 to July ...
user avatar
0 votes
0 answers
18 views

Autocorrelation function of Arima(1,1,0)

I have ARIMA(1,1,0) model: (1-ΦB)(1-B)X_t = ε_t Where ε_t ~ WN(0,σ^2), |Φ|<1, DX_0 < ∞. How do I calculate the autocorrelation function?
user avatar
  • 1

1
2 3 4 5
263