Time series are data observed over time (either in continuous time or at discrete time periods).

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278 views

Multivariant time series in R. How to find lagged correlation and build model for forecasting

I'm new in the page and pretty new in statistics and R. I'm working on a project for college with the objective of finding the correlation between rain and water flow level in rivers. Once the ...
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216 views

$ARIMA(p,d,q)+X_t$, Simulation over Forecasting period

I have time series data and I used an $ARIMA(p,d,q)+X_t$ as the model to fit the data. The $X_t$ is an indicator random variable that is either 0 (when I don’t see a rare event) or 1 (when I see the ...
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222 views

Link Anomaly Detection in Temporal Network

I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
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257 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 ...
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244 views

How to find the functional form of pdf from time series using Kernel density estimate

I will appreciate help in determining the functional form of the probability density function (pdf) for the following case. I have read about Kernel Density Estimate for the case when we don't have ...
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456 views

Stationarity tests for time series

I am currently working on time series modeling, especially on stationarity tests. For this purpose, I am extensively using Pfaff's book "Analysis of integrated and cointegrated time series with R" and ...
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557 views

Simulating time-series given power and cross spectral densities

I am having trouble generating a set of stationary colored time-series, given the covariance matrix (their PSDs and CSDs). I know that, given two time-series $y_{I}(t)$ and $y_{J}(t)$, I can ...
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131 views

What's the probability a rabbit will return to a (certain) forest?

Let's assume we have a forest. And there is a breed of rabbits that is visiting that forest all the time. It is possible to distinguish every individual rabbit. There are devices in that forest ...
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458 views

Asynchronous (irregular) Time Series Analysis

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 ...
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158 views

Examining correlation and long range dependence in time series data with strong diurnal effects

I have data sets of network traffic that exhibit strong diurnal effects making them non-stationary. One of the analysis that I want to run is to show correlation between days. If we chopped up the ...
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262 views

How does pooling and resampling affect variance of sample mean?

Suppose I have $N$ independent random variables $X_n$. I draw a sample of predetermined size $K_n$ from each of them. Denote the average of each sample $\bar{\hat{X}}_n$, and the total number of ...
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578 views

Measure score change over time while accounting for baseline differences

I'd like to test for and estimate group differences in NIHSS (National Institute of Health Stroke Scale) change between hospital discharge and three months after hospital discharge. Because the score ...
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580 views

Exogenous variables in VECM

I found the following posts interesting and I was wondering if any of you guys know of good academic papers that describe methods/relationships of exogenous variables in VECM models. If so could you ...
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48 views

Determining parameters in AR model for non-stationary time series

I am currently trying to fit an AR model to some financial data. The time series $Y_t$ in levels is clearly non-stationary; however it appears the first differences $dY_t$ are stationary (and this is ...
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34 views

“Average” line over irregular log series data

I have simulation data from 1000 runs, plotting some measurable (in this case convergence of the algorithm) as a function of simulation time. Each run produces a discrete set of points ...
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146 views

How to fit log-linear poisson autoregressive mixed model?

I have time-series count data $N_{i,j}$ (population sizes in site $i$ and year $j$) and I want to correlate year-to-year changes with the environmental conditions $x_{i,j}$. For this, I want to fit ...
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101 views

Probability puzzle about zombies

I am thinking about writing a simple game about zombies. I got stuck trying to calculate how many people should become zombies. Here are my conditions: We have a small rural town of 700 people. One ...
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246 views

Detecting statistically significant clustering of continuous values

I'm working with biological sequence data where each position in the sequence has an associated continuous value. I'm ignoring the sequence content so the data is very similar to a time series with ...
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1k views

Interpreting time series decomposition using TBATS from R forecast package

I would like to decompose the following time series data into seasonal, trend, and residual componenets. The data is an hourly Cooling Energy Profile from a commercial building: ...
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205 views

How to design good plots for multiple time series?

I have huge (about 100 000) set of time series. I need to show between 5 to 10 time series, chosen semi-randomly on one chart. Chart estate is very limited - plot for each time series is only 100px x ...
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196 views

Unit root tests and stationarity

Two common methods of testing whether a time series is stationary are the KPSS and ADF tests. If my understanding is correct, these tests essentially work by measuring the residuals of fitting the ...
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113 views

Visualizing probability of event over time, based on epoch time

I have a list of epoch/unix times at which an event happened. My hypothesis is that there are certain times during the week when this event might happen more frequently. How can I visualize/determine ...
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135 views

Reference for implementing generalized likelihood ratio test to determine online whether time-series mean has shifted

What is a reference that describes the "generalized likelihood ratio" test to determine online (i.e., meaning that we add an observation, then check, then add an observation, then check) whether the ...
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128 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 ...
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168 views

Estimating parameters of an unknown PID controller

Say that I have your standard PID controller at work. To keep it extremely simple imagine I have a target $x^*$ on the variable $x$. Then the controller is: $y(t) = K_p ( x^* - x_t) + K_i \int_0^t ...
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571 views

Lag length selection Granger causality test

Consider G-Causality on two stationary time series vectors (call these variables $X$ and $Y$), each with 100+ observations. It's daily financial market time series data. I have reason to believe that ...
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52 views

Estimating a time frame for interventions or judging the extent to which events become “determined” as time goes on

In certain arenas, it's valuable to be able to intervene early on to prevent problems from getting worse, because after a certain point there's not much you can do. Two examples might be public health ...
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183 views

How to analyze mood data over time?

I've collected data for individuals on a team about their daily mood. Each day, individuals rate their mood on a scale that is assigned the following values: 0 (bad), 5 (so-so), 10 (good). Using the ...
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101 views

Confidence intervals for difference in time series

I have a stochastic model used to simulate time series of some process. I am interested in the effect of changing one parameter to a specific value and want to show the difference between the time ...
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374 views

How to model time-varying correlation

Suppose I have two time-series variables, $\{x_t\}$ and $\{y_t\}$, where $t\in[1,T]$. I would like to model the correlation $\rho(x_t,y_s)$ as some function of $t$,$s$, and the difference $t-s$. In ...
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125 views

How to denoise a “Poissonous” time series

I have $N$ time series each of which can be modeled as $$y_{kt}=Ax_{kt}+b+\varepsilon_{kt}\quad(1\le k\le N,1\le t\le T),$$ where $x_{kt}\sim\text{Pois}(\lambda\Delta t)$ and $\varepsilon_{kt}\sim ...
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42 views

Find the median individual with observations on multiple variables over time

I have a question regarding the use of median. We collected data concerning disease development on hosts. We gathered the evolution of three variables over time on individuals. Their characteristics: ...
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195 views

Intervention With Differencing

When conducting an intervention analysis with time series data (aka Interrupted Time series) as discussed here for example one requirement I have is to estimate the total gain (or loss) due to the ...
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76 views

ACF and PACF plot analysis

I am new to ARIMA, and I am trying to understand these lag plots. Are the following ACF and PACF suggesting that the lag of my time series is 4? If I am wrong, please help me understand these plots. ...
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108 views

Fama and French Three Factors: A time series analysis

Is there any literature on whether the three factors in the Fama–French three-factor model follow any kind of time series models, such as multivariate ARMA?
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283 views

Why do I get very different results estimating GARCH-M model in EViews and R (rugarch)?

I'm dealing with a GARCH-M model that I've estimated using R and EViews. Here are its mean and variance equations. Mean equation: $$ y_t=\mu + \rho \sigma^2_t + \varepsilon_t $$ Variance equation: ...
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64 views

Is spurious regression impossible if you include lagged error terms?

If you have a random walk A, and a random walk B, and you regress them against each other you run into spurious regression. In our textbook however is written that it is impossible to have spurious ...
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58 views

Annual time series count data where the dependent variable is a count averaging 3,000 and no zeros

I need your assistance on time series count data. I got some annual time series data I want to run, however the dependent variable is a count (number of deaths) while the independent variables are ...
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247 views

Vector autoregression with exogenous variables

Im dealing with a VAR model where I also want to include exogenous variables. Based on my sampling, the exogenous variables in $t$ are independent from my other variables in $t$, but highly dependent ...
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504 views

Time series clustering: Fourier transform and PCA

I have biological time series (9 years long) of the biomass of species which logically exhibit a seasonal pattern. I would like to cluster them into a few groups based on their typical seasonal ...
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93 views

Predicting for month in R

I'm trying to understand some concepts related to predictive modeling. So let's say that I have the following data sample and am trying to regress sales on ...
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93 views

Averaging Correlations

I am working with patient experience data where patients answer questions regarding their stay at the hospital. Each question is then given a correlation value as it relates to the final "overall ...
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236 views

Regression model of large, correlated, heavy-tailed data

I have a large panel-like data set: about 15,000 individuals, on average 350 time points, two dozen variables (plus some more variables we left out for context-specific reasons). What I want to ...
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375 views

How to calculate p-value for Cross-Correlation for two time series with delay?

I have two stationery time series that I want to see are they correlated or not. I decided to work with cross correlation, there is a good answer in Correlation between two time series but I dont know ...
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137 views

Dealing with missing data in an exponential smoothing model

There does not seem to be a standard way to deal with missing data in the context of the exponential smoothing family of models. In particular, the R implementation called ets in the forecast package ...
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75 views

Determining stability in a time series via probabilistic modeling

I recently started to read Probabilistic Programming and Bayesian Methods for Hackers and really got interested in the topic and PyMC. I especially like the example of the first chapter where ...
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161 views

Algorithm for real-time normalization of time-series data?

I'm working on an algorithm that takes in a vector of the most recent data point from a number of sensor streams and compares the euclidean distance to previous vectors. The problem is that the ...
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159 views

Cointegration structure

I have two time series that I am investigating, acc and amb, the time frequency is daily data. They are both non stationary, as evidenced by the follows: ...
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154 views

Method for calculating percentiles for a set of time series

I have a set of time series for a given quantity (e.g. CPU). The measurements are roughly evenly spaced, but the data points aren't synchronised between sets and some sets have missing measurements. ...
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139 views

Predicting the year computers will be able to do 1 exaFLOPS using historical data (time series forcasting using prediction interval)

Put simply, I need to make a prediction interval (or confidence interval?) for the x value when y reaches a certain number given historical data for x versus y. Long Version: I have data on the ...