0
votes
0answers
3 views

R-package dlm (dynamic regression, dlmRegMod), especially CAPMDLM example… please help me! [migrated]

I am a graduate student in Business. Fortunately, I found a DLMCAPM code (https://github.com/VSRonin/DLMCAPM/blob/master/Final%20Work.R) for a bivariate case in GitHub regarding on the Dynamic ...
1
vote
0answers
36 views

Comparing anomaly detection algorithms

My question is how can different anomaly detection algorithms be compared for my specific dataset. Essentially, I have multivariate timeseries (physical quantities such as temperature, pressure) and a ...
0
votes
0answers
39 views

Large regression models and multivariate model

Large Regression models says that a regression model is large if the signal dimension $p$ is greater than number of observations $n$. In AR(2) model $y_t = a1y_{t-1} + a2y_{t-2}$ the parameter is a ...
0
votes
0answers
12 views

How can I a “multiplier effect” in time series data?

I currently have data corresponding to how often a certain set of songs were downloaded. Each song has a release date, and then the number of downloads per day going forward to today. It would look ...
0
votes
0answers
32 views

Forecasting time series with missing data and irregular intervals

I have a data set of medical drug stock levels at health centres and I want to forecast monthly consumption over the following 3-6 months. However about 30%-40% of the data is missing and some of the ...
0
votes
0answers
11 views

Pattern and most influential parameter detection.

I need some advise to approach the solution. Here is the question. Background: The growth of bacteria, Gb is dependant on 4 factors W, X, Y, Z where W and X --- can take any integer value from -10 ...
1
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0answers
24 views

Interaction in time series analysis

I have three different physiological variables--heart rate, respiratory rate and blood oxygen saturation, each as a time series. I am trying to study the interaction between the variables as they ...
1
vote
0answers
32 views

Reducing high dimensionality as well as feature selection on multivariate time series

Lately I've been reading a lot about time series clustering as I want to search for similar patterns in my own data set. Even though I feel like I understand the basic concepts of this task I still ...
1
vote
0answers
15 views

How to conduct the two sample test with extra data to eliminate between-subjects variability

I am stuck with the correlated and independent data combined in one study. Here's my dilemma: Say X is a drug(explanatory variable) and Y is a gene expression(response variable). Normally, you ...
1
vote
2answers
49 views

Imputing missing observation in multivariate time series

Suppose I have a dataframe consisting of six time series. In this dataframe, some observations are missing, meaning at some timepoints all time series contain a NA-value. In R, one possible imputation ...
0
votes
1answer
43 views

Repeated measures ANOVA design/structural issue

As part of my PhD work, I've conducted an inoculation experiment concerned with marine phytoplankton community productivity (dependant variable, as 'no. of cells') vs nutrient availability. I have two ...
0
votes
0answers
63 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...
1
vote
0answers
67 views

SUTSE DLM on daily mean water & air temperature TS

I have two time series: (1) daily mean water temperature from 1988 to 2014 and (2) daily mean air temperature from 1968 to 2010. The water temperature time series has missing data, occurring on ...
1
vote
1answer
51 views

Model multivariate time series with copula - concepts

I have a question regarding some time series concepts: Suppose I have some "time series" data with cross correlation. Suppose I am able to fit a copula, say to capture dependencies between data of ...
1
vote
0answers
67 views

Ljung–Box test for a multivariate time series?

From Tsay's Analysis of Financial Time Series, For a univariate weakly stationary time series $r_t$, its sample autocorrelation function $\hat{\rho}_l$ is defined as: and the Ljung-Box test is ...
0
votes
0answers
44 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
54 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
vote
1answer
56 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
167 views

Multivariate Time Delay Neural Network: Built-In Matlab Code?

I was wondering if anyone knew if there exists built-in Matlab code for the above mentioned model? Here is the single-variate case: http://www.mathworks.com/help/nnet/ref/timedelaynet.html I tried ...
0
votes
0answers
20 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
29 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
534 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 ...
1
vote
1answer
163 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
206 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
175 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
1answer
63 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
710 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
21 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
125 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
82 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
244 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
229 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
180 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
454 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
3k 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
273 views

Relationship between $R^2$ and MAE in forecasting

I have the following linear model based on multivariate timeseries: ...
6
votes
1answer
446 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
695 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
98 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
253 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
743 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
496 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
463 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
901 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
353 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
259 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 ...