In field of economics (I think) we have ARIMA and GARCH for regularly spaced time series and Poisson, Hawkes for modeling point processes, so how about attempts for modeling irregularly (unevenly) spaced time series - are there (at least) any…
RNNs are remarkably good for capturing the time-dependence of sequential data. However, what happens when the sequence elements aren't equally spaced in time?
E.g., the first input to the LSTM cell happens on Monday, then no data from Tuesday to…
It isn't clear to me how to calculate cointegration with irregular time series (ideally using the Johansen test with VECM). My initial thought would be to regularize the series and interpolate missing values, although that may bias the…
I am impressed by the R forecast package, as well as e.g. the zoo package for irregular time series and interpolation of missing values.
My application is in the area of call center traffic forecasting, so data on weekends is (nearly) always…
In financial econometrics research, it is very common to investigate relationships between financial time series that take the form of daily data. The variable will often be made $I(0)$ by taking the log difference, for example;…
I have been reading a lot about Dynamic Time Warping (DTW) lately. I am very surprised that there is no literature at all on the application of DTW to irregular time series, or at least I could not find it.
Could anybody give me a reference to…
I asked this question over on StackOverflow, and was recommended to ask it here.
I have two time series of 3D accelerometer data that have different time bases (clocks started at different times, with some very slight creep during the sampling…
There are several methods to make forecasts of equidistant time series (e.g. Holt-Winters, ARIMA, ...). However I am currently working on the following irregular spaced data set, which has a varying amount of data points per year and no regular time…
I am trying to analyze the lead-lag between time series of two stock prices.
In regular time series analysis, we can do Cross Correlaton, VECM (Granger Causality). However how does one handle the same in irregularly spaced time series.
The…
I have data for the population of a number of different fish, sampled over a period of about 5 years, but in a very irregular pattern. Sometimes there are months between samples, sometimes there are several samples in one month. There are also many…
I have an irregularly spaced XTS time series (with POSIXct values as index type).
How can I build a new time series sampled at a let's say 10 minute interval, but with each sample moment aligned to a round time (13:00:00, 13:10:00, 13:20:00, ...).…
I would like to apply Kalman smoothing to a series of data sampled at irregular time points. There is a claim on Stack Exchange that "For irregular spaced time series it's easy to construct a Kalman filter", but I haven't been able to find any…
I have a dataset of water temperature measurements taken from a large waterbody at irregular intervals over a period of decades. (Galveston Bay, TX if you’re interested)
Here’s the head of the data:
STATION_ID DATE TIME LATITUDE LONGITUDE…
I don't really know what's possible, and would like a pointer in the right direction.
I have measurements of time and position which could be anything from a person walking, a vehicle on a road, or in a car park, or a printer in an office. I need…
I have a few time series that were (for technical reasons) acquired with slightly different time intervals, ranging between 19 and 21 seconds.
Now, I would like to average the values of these different time series over time, so I thought that I…