Questions tagged [unevenly-spaced-time-series]

Time series sampled or measured at unevenly (or irregular) distributed time points.

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

Similarity index between 2 unevenly sampled time series

Say I have 2 time series $s_1$ and $s_2$ with independent variable $x_1$, and dependent value $y$. These 2 series are not evenly sampled across $x_1$, or even sampled at the same rate. Now, I have ...
1
vote
0answers
17 views

Forecasting with Irregularly Missing Data

Suppose I am supplying $N = 1000$ vendors, and I am looking for a way to predict their demand for my product over $T = 90$ days. Concretely, I hope to take some features for each vendor, such as their ...
0
votes
0answers
18 views

Event-based time-series analysis

I'm trying to find patterns in a game event that happens randomly over time. The data looks like this: ...
0
votes
0answers
25 views

Linear Mixed Effects Models - Time dependent covariates with irregular sampling

I've been looking at using a linear mixed effects model to describe the change in a biomarker $y$ over time in a large number of people over a time period $T$ (measured until an event happens). I want ...
0
votes
0answers
18 views

Equalize multiple unevenly spaced time series for forecasting

I am building a time-series forecasting model to predict some patterns in climatological data. The dataset consists of many (2 mln) time series which look for example as: However the observations ...
0
votes
0answers
33 views

Extended Kalman Filter with irregular intervals

I am trying to work out how the EKF applies if samples come at irregular time intervals. I found the post here: How does one apply Kalman smoothing with irregular time steps? But I did not ...
0
votes
0answers
38 views

Comparing time series data with different interval

I have time series data for one day (temperature) measured every 5 seconds and would like to increase the period between measurements and somehow calculate the level of error/similarity/correlation (I'...
0
votes
1answer
26 views

How to detect a drop in regularity / increase in spontaneity of time data?

I have been tasked with detecting changes in regularity for multiple datasets. Each dataset is linked to a different type of event, and each dataset consists of a few hundred timestamps representing ...
3
votes
2answers
49 views

Correlation between two time series of very different frequency?

I am wondering if there is a limit to calculation of the correlation between two vectors symbolizing events of VERY different frequency. A = events that can appear in the millisecond area B = events ...
0
votes
0answers
20 views

multi-step forecast classification problem

There are multiple approaches for multi-step time series forecasting, mainly recursive strategy, independent and MIMO. If I want to predict whether an event is going to occur at some point in the ...
0
votes
0answers
30 views

Time series “window” terminology

I've been reading about time series analysis/prediction and there're some things about its terminology that aren't still clear to me. For the following definitions, suppose that we're only interested ...
1
vote
0answers
21 views

Customer next visit behavior forecast

I'm currently working with retail data about a store and the goal is to predict when each customer will visit the store again e.g customer id = 1 will probably visit again in 6 days(recency) My ...
0
votes
0answers
15 views

Modeling unequally spaced time series as OU process

I have a time series wherein the data points are unevenly spaced. I read this can be modeled as discrete time observation from a continuous time process. So I am trying to model it as an Ornstein-...
1
vote
1answer
36 views

Scale of time covariate in `corCAR1()` matters?

I'm running a bunch of GAM analyses on time series data (measurements of my own weight). Unlike many examples I see online, my data is not spaced evenly in time. In fact, time points can come minutes ...
0
votes
0answers
32 views

Forecasting using unevenly sampled data

We have some head position data obtained from the sensors of a Virtual Reality headset. First 200 ms of the data from one user measured while watching one 360-video sequence looks like as follows: <...
3
votes
2answers
85 views

How to forecast number of event occurences in a certain time period?

I am attempting to predict how many times a certain event will happen in a time period. For instance, predict the number of time the event will occur in the next 5 hours. I have data going back a ...
0
votes
1answer
14 views

Mean time to event with uneven follow up times

I'm trying to compare the effect of two treatments on the time to fracture healing, and came across a study that does the following: They compared effect of treatment A vs treatment B on fracture ...
0
votes
0answers
17 views

Between Group comparison for parameters measured on different time points

I have a dataset of 100 patients for whom data was recorded of 3 different parameters say Heart rate, temperature and ETCO2 levels which are measured in 3 phases eg. Phase 0, Phase 1 and Phase 2. The ...
0
votes
1answer
27 views

Tackling challenging semi-weekly or weekly data with gaps

I am working on ferry itineraries (i.e. tickets sold in a specific itinerary). Consider the scenarios: 1) itinerary taken only on Tuesdays and Thursdays every week ( but with gaps - depending on ...
1
vote
0answers
65 views

Missing as opposed to non existent data in time-series forecasting

Suppose you have a set of observations that occur at regular intervals in time, but containing regular gaps during which there is no data, not because it is hidden or missing, but because the ...
3
votes
0answers
91 views

Handling non-uniform frequency data

I have some medical data (heart rates) at non-uniform intervals (usually readings every few min at the start of the study and several readings a minute toward the end). The timing and when the change ...
0
votes
0answers
19 views

Vector Time Series: Capturing Systematic and Nonsystematic Patterns in Multiple Datasets | Financial Option Data

How does time series work with multiple time series data sets on the same index? For example, suppose I were a utilities company. Suppose I have the electricity usage of two homes, each indexed for ...
0
votes
0answers
19 views

Standardize Time Series Intervals in R

I have a time series that has data taken at irregular time intervals, and I would like to standardize the time intervals so that I can perform analysis such as detrended fluctuation analysis (which ...
1
vote
1answer
210 views

Notation for unevenly-spaced to evenly-spaced time series conversion

I have an unevenly-spaced time series. To make it evenly-spaced, I resample the time series to a larger timespan (e.g. day) and sum up all values within this time frame. In Python (and pandas) it is ...
0
votes
0answers
20 views

How to select features for predictive model from temporal dataset with irregular measurements?

I have a series of measurements taken of water pollution on a roughly weekly basis at different locations. In total there is a measurement every 3 days at a different location. I have series of ...
1
vote
1answer
167 views

How to deal with unevenly spaced time data in time series linear regression

I have a dataset that has a number of instances that look like the following: ...
1
vote
1answer
68 views

Practical handling of Dynamic Time Warping for time-series with unequal sampling frequency (irregular time series)

Hi all and thank you for taking time to read this. When I read the general literature about dynamical time warping (and the vignette for the $\texttt{R}$ package $\texttt{dtw}$), the time series seem ...
1
vote
0answers
23 views

Representing Multiple Variables Measured at Multiple Independent Times

I'm attempting to find a good storage/data representation in "R" for a data set with a large number of variables, each of which is measured independently for a number of years but at irregular ...
1
vote
1answer
47 views

How to calculate correlation for 2 time series where the tick times do not line up

I'm looking to compute intraday correlation for 2 tick by tick intraday commodity price time series. The tick times do not line up across the 2 time series. I'm thinking of converting the time ...
1
vote
1answer
82 views

How to check if a data is poisson sampled?

I was reading one article which develops a theory for the Poisson sampled data. That is the data is collected over time-points $\{T_k, k>1\}$, which are jump-moments of a homogeneous Poisson ...
0
votes
1answer
125 views

How to model time series with unevenly spaced observations?

I have three time series of the following form: $T = T_{2000}, T_{2004}, T_{2008}, …$ $U = U_{1998}, U_{1999}, U_{2000}, U_{2001}, U_{2002}, U_{2003}, …$ $V = V_{1998}, V_{1999}, V_{2000}, V_{2001},...
1
vote
0answers
43 views

Classify time series with unequal lenghts [closed]

I have a set of time series sensor measurements (acceleration and gyroscope readings) for driving events (harsh acceleration, harsh brake …) with the type, start and end of each event. I need to ...
0
votes
0answers
91 views

Why ARMA models works on assumption of uniformly sampled time series?

I am dealing with irregularly spaced time series data. I have been reading papers how ARMA based approaches can be used for time series forecasting. However, ARMA assumes uniformly sampled time ...
1
vote
0answers
53 views

Smoothing with non-regular observations

If we have data that changes continuously in time, and we sample this data at regular intervals - i.e. we get samples $x_0$, $x_1$, $\dots$, where the time $\Delta t$ between taking samples $x_i$ and $...
4
votes
3answers
395 views

Binary target prediction using LSTM with sparse events in time

I have a data of patients that have multiple events happening in there medical history, I'd like to predict a target of having a specific targeted-event in the next 30 days. The data is timestamped ...
1
vote
1answer
184 views

R: generalised additive model on proportional data

Introduction I am analysing temporal population data on the amphipod Orchestia gammarellus. At several moments each year, all animals were collected from a small spot, and several life history traits ...
1
vote
1answer
87 views

Machine Learning techniques for uneven series of events

I don't know the correct terminology and so long everything I typed into google lead me to some version of time series modeling where all time series had the same number of points in a given time ...
0
votes
1answer
490 views

Detecting leading stocks using lag correlation

I am working on a project to find leading stocks in a stock market by using lag correlation. Say I want to compare 2 stocks, X and Y, and I have the time series of stock prices. Assume that the time ...
3
votes
2answers
53 views

Example of dataset where the data collected at time-points $g(t_1), g(t_2), \ldots$

What would be some practical scenarios where we collect data at time-points $g(t_1), \ldots, g(t_n)$, where $g$ is an increasing function? For example, $g(t) = \exp(t)$ or $\ln t$. To be more clear, ...
0
votes
1answer
710 views

LSTM - random and always-different time between data measurements?

I am working with a time series problem where the time between two data measurements is random, and I am trying, without luck, to find an LSTM architecture that can handle this. A very simplified ...
1
vote
0answers
255 views

Calculating variance and standard deviation of continuous time series

I am trying to calculate the variance and standard deviation of an unevenly spaced continuous time series. Example data: ...
0
votes
2answers
65 views

Forecast sales and then ungroupto find individual sales

I am trying to solve a problem for a brewery: A brewery has 50 beer types in total out of which only 8 to 10 beers are available on tap for a single day i.e only 8 to 10 beers will be sold on any ...
2
votes
2answers
508 views

Dealing with missing data in Time Series or non-constant time intervals for forecasting in R (ARIMA, Holt Winters, Theta)

I have a time series of sensor data from a machine. This machine is sometimes moved and thus there are big chunks of missing data, here is a plot of the data points: My goal is to try to start ...
2
votes
0answers
44 views

Machine Learning on Sequential Data Reperesenting Events

Would you please recommend which model should I use for modeling user activity observing certain events that happen to them in time. I want to make sense of the history of events (just a presence of ...
5
votes
2answers
1k views

How to find out if two time series correlated? they are of not equal length and with unknown delay between cause and effect, irregular log time?

Writing the whole problem, to avoid asking a question when in reality I needed an answer to a whole different question, and just didn't know how to ask. I have a lot of data about my daily life and I ...
1
vote
0answers
295 views

Forecasting with ARIMA models and sensor data in R

I'm trying to apply ARIMA models to sensor data and would be thankful if anyone could answer my questions. I should add that I have very little experience with time series (trying to change that). ...
1
vote
0answers
31 views

Comparing rates of change with unequal and unevenly spaced timepoints

I am trying to compare rates of change in my data and although the units of time are the same, some instances have more/less time points than others and the time points are not uniform. Is there some ...
1
vote
1answer
480 views

Time Series Classification with Varying Sampling Frequency

I'm new to signal processing and am wondering how to deal with a time-series classification problem when I have unequally spaced data. Skimming through recent literature, including The great time ...
4
votes
0answers
138 views

Tests of stationarity in irregularly (unevenly) spaced time series

I need to do check if my time series data is stationary or not. However, the data is so irregular that cannot be transformed into evenly spaced. Any suggestion?
2
votes
0answers
336 views

R- How to find the trend of irregular time series?

I'm working on marine fish ecological data, on an irregular time scale with data only for 1993,1994,2006,2007,2009,2014,2016 and 2017. For each year, I have computed several taxonomic and functionnal ...