Skip to main content

All Questions

Tagged with
Filter by
Sorted by
Tagged with
1 vote
0 answers
15 views

Finding the most important daily pattern on a time series

I have multiple hourly time series measurements from different measurement points, for multiple weeks. My goal is to eventually cluster the measurement points into clusters, but to reduce ...
Jim A's user avatar
  • 11
0 votes
0 answers
17 views

Declustering impact, stationarity and discretization

I have a seasonal time series, and I am considering declustering (before any other preprocessing steps) it using runs declustering. If I observe an extremal index of 1, can I claim that my data is i.i....
Thoms's user avatar
  • 1
2 votes
0 answers
24 views

Quantifying a Sequence of Binary Outcomes

I'm compiling a dataset on animal color patterns. Blotches flank the body of the animal (Agkistrodon contortrix) and meet along its midline (i.e., spine). At midline, the blotches can join ...
Ross Couvillon's user avatar
0 votes
0 answers
24 views

Curse of dimensionality in Time series with K-means

I have been looking at the following notebook: time series clustering where the writer says that the dataset is affected by the "Curse of Dimensionality", so applying TimeSeriesKMeans ...
Zackbord's user avatar
0 votes
1 answer
51 views

Problems Determining Optimal Cluster Number for Time-Series Data

I'm facing problems with determining the right number of clusters for my 2D time-series data. I have a numerical simulation that outputs a time-series of 2D grids that represent a mass density ...
Double Descent's user avatar
0 votes
0 answers
40 views

Clustering and segmented regression interrupted time series analysis

I would like to perform an interrupted time series analysis to look at the impact of the pandemic on cancer incidence using individual level data. I plan to use a negative binomial segmented ...
user405452's user avatar
0 votes
0 answers
51 views

Identifying states (or clusters) in multivariate mixed-type time series

I have multivariate time series with mixed data types, which includes continuous variables, binary variables, and variables with bimodal distributions. I need to identify distinct states or epochs in ...
graavit's user avatar
1 vote
0 answers
48 views

Clustering for a meaningful fixed effects model

I have panel data for 5 time periods and about 10,000 geographic units. My dependent variable Share is the share of workers in a specific category, and my descriptors represent various factors that ...
Mikhail's user avatar
  • 97
0 votes
1 answer
47 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. ...
tms's user avatar
  • 1
2 votes
1 answer
94 views

Inconsistent cluster indices using hierarchical clustering for time series data

I am currently trying to spatially cluster data that is ordered on a grid. Each point has x and y coordinates as well as a measurement value. These features come from a time series where I analyze ...
Krautsultan's user avatar
0 votes
0 answers
89 views

Silhouette Score for ordered clusters

My clusters are arranged according to a time series, and I want to compute the silhouette score for the clustering performed, considering that they follow an order. Therefore the nearest cluster to ...
sp29's user avatar
  • 101
1 vote
0 answers
73 views

Methods describe the temporal consistency of kernel density data

I am working on a spatial time series analysis project. The task is to study the spatial distribution of point features (e.g., crime events, traffic accidents) over time. I aim to find the places with ...
Bright Chang's user avatar
1 vote
0 answers
17 views

truncated Functional data analysis + identify subgroups?

I have intensive longitudinal data about heartbeat rates, movement activity measured by actiwatch, respiration rates etc... collected from about 100 patients at a terminal care. For each patient, data ...
ReiMon's user avatar
  • 21
2 votes
2 answers
1k views

Time series clustering on large data

I am trying to do K-means clustering on my data which has time series length of 3700 and for (latitude,longitude) points of around 6000 in length. However, timeseries clustering using tslearn package ...
Vinayak Huggannavar's user avatar
1 vote
1 answer
604 views

Comparing clustering methods based on internal Cluster Validity Indices

I have used the R package dtwclust to generate clusters for more than a thousand time-series objects.Since I did not have any prior information on the number or validity of clusters, I used a suite of ...
Mansi's user avatar
  • 41
0 votes
1 answer
108 views

Time Series clustering: clustering a dictionary of time series

I'm working on classifying times series to find clear pattern of use. My data is collected from clients of a telecom company, and we want to detect pattern of the amount of data consumed by clients ...
Ilias ETTOUKI's user avatar
0 votes
1 answer
112 views

Time Series clustering: Changing warping window for Dynamic time warping

I'm working on the same type of data and i want to classify the times series to find clear pattern of use. My data is collected from clients of a telecom company, and we want to detect pattern of the ...
Ilias ETTOUKI's user avatar
1 vote
1 answer
346 views

Clustering Data with Time and ~10 million records

I have a dataset with features like product categories, their dimensions, price, units sold on a given day. I want to create clusters out of this dataset (~12-15 million records) and I am using data ...
Shivam Bindal's user avatar
0 votes
0 answers
279 views

clustering approach to identify temporal "states" within time-series in R

I am working on a problem where I have a multiple time series, each with a size of a 100 steps, each being described by a 8 variables variables. I want to identify "states" within each time ...
Myriad's user avatar
  • 221
1 vote
0 answers
21 views

Visualizing and clustering user activity within tool ecosystem

I have a large amount of telemetry for a population of users using a tool suite. In many cases, users are working on a number of different tasks over the course of a day, and hopping back and forth ...
soandos's user avatar
  • 111
1 vote
0 answers
122 views

Cluster analysis of time series data with a few points in time

I have asked the question here before but have not been able to resolve it. I have data from 150 participants who were asked about their emotional state at 3 points in time. There are 28 different ...
user52112's user avatar
0 votes
1 answer
23 views

Method for identifying surges in multi-year inbound 911 call data

I have a dataset which consists of calls placed to 911 occurring over a period of 13 years. The annual total calls has increased significantly over time, starting at around 200000 per year, and then ...
Rich Harrington's user avatar
3 votes
2 answers
591 views

Models for describing cluster change over time

Suppose I have a set of observations encoded as a matrix $X$ whose entries $X_{it} \in \mathcal{C} $ correspond to cluster labels of experimental unit $i$ with repeated measures at time $t$, where $\...
fool's user avatar
  • 2,540
1 vote
1 answer
823 views

Cluster on variable-length time series

I have a series like this: list_1 = [5,3,6,7,8,9,0,5,5,2,4,66,7] list_2 = [6,39,6,4,7] I would like to know Is all list_2 or subsequence ...
Toan Nguyen Phuoc's user avatar
2 votes
1 answer
551 views

PCA to select few stocks to mimic and index

I am looking for a way to select a subset of stocks which returns can approximately mimick the return of an 'index' they corresponds to. These are all self created factor portfolios, and not traded ...
Nicolaj Jeppesen's user avatar
1 vote
1 answer
721 views

How to cluster univariate time series

I have different univariate time series and the goal is to detect outliers automatically. Therefore I used different algorithms for different time series. But the first step would be to detect ...
Christian's user avatar
  • 113
0 votes
1 answer
67 views

Clustering methods for regional temporal clusters

I have observations of individuals over time, where they either experience -1, +1 or mostly 0, like so. ...
SimonDude's user avatar
0 votes
1 answer
73 views

Clustering points in time series

I have time-series data - Temperature Vs Time. The temperature raises during regular intervals and stays high for some time before returning to a normal value as shown below. I would like to identify ...
Sky's user avatar
  • 103
2 votes
1 answer
1k views

K-Means Clustering of time series in R

I want to create a cluster of K-Means of time series with R but I don't know where to start. Could you recommend some articles or tutorial?
Maria MJ's user avatar
5 votes
1 answer
102 views

Definition and Taxonomy of Seasonal Time Series

I want to categorize a large number of time series into non-seasonal and seasonal divide the seasonal ones into a small number of subgroups by type of seasonality Are there any formal definitions/...
dimitriy's user avatar
  • 38.3k
0 votes
1 answer
727 views

Applications of Dynamic Time Warping (Time Series) [closed]

Recently, I came across this algorithm called "Dynamic Time Warp" (e.g. https://cran.r-project.org/web/packages/dtw/vignettes/dtw.pdf). Although this algorithm looks quite involved and ...
stats_noob's user avatar
0 votes
1 answer
74 views

Assigning Thousands of Time Series to Two Similar Groups

I have thousands of time series that I wish to assign to one of two groups such that these two groups, in the aggregate, are as 'similar' as possible (maximising the coefficient of correlation between ...
Three14's user avatar
  • 13
2 votes
1 answer
793 views

Applying Dynamic Time Warping (DTW) instead of Euclidean Distance for Clustering Synchronized Time series data

I am trying to cluster members based on hourly login data. As this is mostly synchronized, I first applied Euclidean and it failed to cluster them into groups with sensible patterns. I tried DTW ...
Sunny's user avatar
  • 21
0 votes
1 answer
1k views

Clustering time series of unequal length using DBSCAN and DTW

I'm working on a dataset of all visits generated by email campaigns that were sent in 2020, and the goal is to develop a clustering model that groups similar campaigns (trend line similarity) together ...
Adib's user avatar
  • 135
0 votes
0 answers
46 views

Distance from centroid infinite in time series clustering (K-Shape)

I am trying to do time series clustering with R library dtwclust, and more specifically the k-Shape algorithm. I have almost 100,000 time series with 28 time points ...
adrian1121's user avatar
  • 1,136
1 vote
0 answers
28 views

Standarizing over variates on multivariate time series

I want to run a clustering algorithm (means with multidimensional euclidean distance) on multivariate time series. Each variate of the time series has different units so it needs to be normalized. I ...
epalto's user avatar
  • 33
0 votes
0 answers
30 views

How meaningful are the results when you difference the time series dataset before clustering?

On a certain task where I need to perform K-Means Time Series Clustering with DTW algorithm, I would like to know how credible the results are when performing clustering on the original vs a dataset ...
Karen's user avatar
  • 101
0 votes
0 answers
302 views

Cross correlation of time series in a cluster

I have 15000 time series each of length 288 (corresponding to a sample taken every 5 minutes during a single day), and I want to group these time series by how similar they are based on shape and y-...
derNincompoop's user avatar
2 votes
0 answers
46 views

Detect distinct populations in irregular time series

I have two distinct classes, A and B both with property X. At irregular intervals I receive a measurement of X, without knowledge of whether it is a measurement from A or B. The true value of X for A ...
Josh's user avatar
  • 21
0 votes
1 answer
120 views

How should I do clustering when I have a mix of single-element and time series features?

I'm trying to cluster together different short audio files based on the zero-crossing rate (an integer) and the energy, spectral centroid, and spectral bandwidth (time-variant values). I've decided ...
Jodast's user avatar
  • 155
1 vote
0 answers
32 views

Need help specifying my problem: time series segmentation with clustering?

I can't get any further with my segmentation/clustering/classification problem and need help in choosing the right tools, or rather in leading me to the right problem definition. I have a single long ...
Konrad's user avatar
  • 11
1 vote
1 answer
118 views

Detect spans of consecutive values with average over certain limit [closed]

I have weekly data for volume of product ordered by any customer. I want to identify the longest span of consecutive weeks such that the average of that span is >= 33,000 (approximate; up to -2000 ...
Shree's user avatar
  • 121
2 votes
1 answer
360 views

Discovering peaks/patterns in time-series and clustering them

I have a dataset which contains minute level sensor measurements. Sample is shown here: To me useful information are these peaks in time series, mostly their peak and duration. My idea is to take out ...
SirDawar's user avatar
1 vote
0 answers
304 views

ARCH coefficient in GARCH models

Is anyone knows to interpret ARCH Coefficient in GARCH Models ? I tried to find what is ARCH Coefficient means. Some says it's for detecting Spillover effect, Some says Volatility Clustering or ...
Yolla Haifah's user avatar
1 vote
0 answers
457 views

Best practice/Ideas for clustering Event Sequence Embeddings?

My dataset consist of around 40 000 samples of event sequences. Sample of data [[Event 1, Event 2, Event 4, Event 5], [Event 1, Event 3, Event 4], [...]] I ...
kspr's user avatar
  • 171
1 vote
1 answer
32 views

Cluster before or after de-trend the data for time series data

I am working with a non-stationary time series finance data set. I would like to perform a clustering method on the data. My questions are, Do I need to de-trend the data first and then cluster it, or ...
Maryam's user avatar
  • 1,680
6 votes
1 answer
4k views

How to cluster non-aligned time-series with different length?

I am trying to cluster dozens of time-series sampled every 30min, and which cover the period mid2016 - mid2020. Most of them have very nice "patterns", others may have missing values for a ...
yoyoog's user avatar
  • 359
3 votes
2 answers
133 views

Categorizing river discharge data

I'm struggling with figuring out the best way to break up my river discharge data in a way that I can use it as a factor for further analysis. I'm currently manipulating the data in R but plan to pull ...
fishchick's user avatar
1 vote
0 answers
3k views

Silhouette Score not robust when clustering time series with tslearn

I have 40 univariate Time series which I am clustering with tslearn. To determine a reasonable amount of clusters, I use the silhouette coefficient. However, I noticed that it is extremely unrobust, ...
bk_'s user avatar
  • 341
2 votes
1 answer
176 views

K-Means on Time Series but each timestep is considered an individual point

As stated in the question, I have a doubt about the possibility that K-Means would work if we apply it on one time series where each timestep is considered an individual data point. Please allow me to ...
Elise Le's user avatar

1
2 3 4 5