0
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0answers
34 views

Keywords to find academic lectures on multivariate time series analysis on youtube

If I search for "HOTT homotopy type theory" on youtube, I find numerous (advanced/state-of-the art) academic lectures on the topic. For instance the following lectures are found on youtube: ...
1
vote
1answer
50 views

Is this multivariate normal? 2 time series linked by a common process

Summary: Consider a scenario where you observe the inputs ($X$) to and outputs ($Y$) from a process ($B$). If I have a model describing how $X$ evolves over time, and a similar model for $Y$, how do I ...
1
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1answer
45 views

Detecting 'causality' in Likert-time series data

[Note] I've decided to re-write my question for the sake of brevity. The original question can be found below. Suppose a number of individuals fill in a questionnaire at a multiple number of time ...
0
votes
0answers
19 views

checking for autocorrelation with many observations and few time periods

How would I go about checking for autocorrelation if I had a few thousand observations for each time period and had about 15 different time periods? The data set I am working with has a lag variable ...
0
votes
0answers
27 views

In case of multi-time series data, does the significant linear model gives there is something more?

I have total of 9 time series data. I'm basically using 8 variables as my X and 1 variable as Y. I've tried VAR model today but I don't see ANYTHING. However, when I do linear regression, all of the ...
4
votes
1answer
150 views

Differences between clustering and segmentation

I have read about piecewise aggregate approximation (PAA) mining time series data, sliding window, top down and bottom up approaches for time series segmentation but these are applicable to single ...
0
votes
1answer
111 views

Outlier treatment in Vector Autoregression (VAR) Model

Data: Multivariate Time Series, Series 1) Demand of a product 2) Rainfall data both available at monthly level from 2010-2013. Approach: I am trying to estimate the effect of rainfall on demand of ...
2
votes
1answer
144 views

Temporal autocorrelation in perMANOVA?

I have a data set where samples are collected once per year for 15 years at a number of sites. I am worried that these data are temporally autocorrelated and was trying to figure out if I need to ...
1
vote
1answer
142 views

How to map a trajectory to a vector?

I have a series of data points in this form (timestamp, lat, long) for a set of users. Each user has a trajectory when he travels from point A to point B. There might be any number of points from A to ...
0
votes
0answers
127 views

Model-based clustering of multivariate time series with R package MFDA

I am trying to cluster multivariate time series (several thousands of them) according to the approach described by Yang et al. in the article "Preprocessing Time Series Data for Classification with ...
0
votes
1answer
61 views

Simulated single value based on multiple chains in RJAGS

I am using RJAGS to simulate the posterior distribution of event that a certain candidate will win the presidential election. I need to find the actual percentage that one of the candidates will have. ...
7
votes
5answers
596 views

Smoothing 2D data

The data consist of optical spectra (light intensity against frequency) recorded at varying times. The points were acquired on a regular grid in x (time) , y (frequency). In order to analyse the time ...
0
votes
0answers
20 views

the approach for checking whether a process is stable?

I have two scenarios for time series data. 1) I have a uni-variate variable spanning across the time axis, are there any approaches or statistic to check whether this process is stable? 2) I have a ...
4
votes
0answers
119 views

Relationship between LASSO T and LARS number of steps k

We can see on the figure (cf Least Angle Regression p30, Efron, Hastie, Johnstone, Tibshirani - link: Least Angle Regression) that there is a direct relationship between: LASSO T absolute norm of ...
2
votes
0answers
74 views

Effect of duration of treatment on the outcome at different time points

I am interested in knowing if the duration of treatment has an effect on treatment with two different drugs. We have used two different drugs to treat cerebral ischemia (brain damage) and continued ...
6
votes
0answers
206 views

Clustering & Time Series

I have a multivariate dataset that changes over time. I have extracted (and normalised) some features and used k-means to generate clusters over the entire span of the dataset. Now I want to see ...
0
votes
1answer
210 views

Testing threshold cointegration in vector error-correction models

In Hansen and Seo's paper on Testing two regime threshold cointegration in VECM (J. Econometrics, 2002; 110:293), the authors proposed a test based on Lagrange Multiplier for testing treshold in ...
1
vote
0answers
165 views

Projecting factors, forecast, using SVD and VAR

I'm curious whether something I tried makes sense statistically... I took a pile of time series inputs and performed an SVD. I want to predict variable Y on the basis of its own time series, and the ...
0
votes
0answers
363 views

Efficient method/technique to update covariance matrix

A covariance matrix of multivariate random variable can be constructed given a time-series random variables. Eg. If you observe a student's performance in different objects (Math, English, Physics, ...
3
votes
1answer
2k views

What is the purpose of and how to use the xreg argument when fitting ARIMA model in R?

I am really new with R and time series. But, I have understood most concept. Part where I am (very) confused is the xreg= argument in ...
0
votes
0answers
233 views

Relationship between $R^2$ and MAE in forecasting

I have the following linear model based on multivariate timeseries: ...
5
votes
1answer
343 views

Least stupid way to forecast a short multivariate time series

I need to forecast the following 4 variables for the 29th unit of time. I have roughly 2 years worth of historical data, where 1 and 14 and 27 are all the same period (or time of year). In the end, I ...
5
votes
3answers
2k views

How to compute the Kullback-Leibler divergence when the PMF contains 0s?

I have the following timeseries obtained using the data posted below. For a sliding window size of 10, I am trying to compute the KL-divergence between the PMF of values within the current sliding ...
7
votes
1answer
643 views

Alternative to block bootstrap for multivariate time series

I currently use the following process for bootstrapping a multivariate time series in R: Determine block sizes -- run the function b.star in the ...
0
votes
1answer
97 views

What metric should I use to determine a significant effect?

I am not a statistician and hope someone can point me towards the right direction. I have some time series data grouped into three classes like this: ...
4
votes
2answers
231 views

Statistics for multi-test replicated correlation analysis

I'm analyzing pairwise correlations of time series between two different types of microarrays done for several samples as biological replicates. So, I have M1 number of variables on type 1 array, M2 ...
0
votes
3answers
646 views

Multivariate random walks in BUGS

I want to jointly estimate a very simple MV-Normal two-dimensional AR[1] process, $[x_t,y_t]=[x_{t-1},y_{t-1}]+\text{[Bivariate Gaussian error]}$, in BUGS. But the syntax has been impossible to ...
6
votes
1answer
458 views

Canonical correlation analysis and time series analysis

Is there a way to utilize Canonical Correlation Analysis when your data are time series and repeated measures (i.e. your experimental units are not independent)? How might one approach the analysis ...
7
votes
2answers
1k views

How to model time-series temperature data at multiple sites as a function of data at one site?

I am new to time series analysis, and would appreciate any suggestions on how best to approach the following time-series regression problem: I have hourly temperature measurements at approximately 20 ...
4
votes
4answers
438 views

Combining 2 sets of coefficients, weighting one of the sets

I have two sets of coefficients from similar data taken at different times. What I want to do is combine the two sets of coefficients giving greater weight to the more most recent set. The goal is ...
6
votes
3answers
765 views

What to make of explanatories in time series?

Having worked mostly with cross sectional data so far and very very recently browsing, scanning stumbling through a bunch of introductory time series literature I wonder what which role explanatory ...
6
votes
1answer
237 views

Is there a method to find what is a good sample size for a VAR-model?

This question might be way off base as I am just getting to know vector autoregressive models, but I've tried searching through the usual channels and if this actually is a valid question it might be ...
7
votes
2answers
246 views

General approaches to model car traffic in a parking garage

a friend of mine has asked me to help him with predictive modelling of car traffic in a medium sized parking garage. The garage has its busy and easy days, its peak hours, dead hours opening hours (it ...
9
votes
3answers
1k views

Intervention analysis with multi-dimensional time-series

I would like to do an intervention analysis to quantify the results of a policy decision on the sales of alcohol over time. I am fairly new to time series analysis, however, so I have some beginners ...
10
votes
5answers
2k views

SVD dimensionality reduction for time series of different length

I am using Singular Value Decomposition as a dimensionality reduction technique. Given N vectors of dimension D, the idea is to ...