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

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stationarity in time series

I'm learning a Time series course and I have a few questions. Strictly stationary is a process if the joint distribution of $X_{t1},X_{t2},...,X_{tm}$is the same as the joint distribution of ...
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How to fit a series into another one so that their mutual information is minimized?

I am building a multivariate model of an output series. I have many series-candidates for inputs. I want to select the inputs based on the mutual information between these inputs and the output. My ...
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21 views

Glue time series back together

I have a long time series whose distribution I don't know. I take snapshot of a fix window at random places of the time series to get a set of equal length shorter time series. Now without the help of ...
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Do we fit this time series data with time series model or spline?

Basically, I have the following data with the number of item A on the vertical axis and the time on the horizontal axis (from 1st hour to the 24th hour). I don't have much experience in fitting a ...
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27 views

Time series and ACD model

When we say fractional gaussian noise is subordinated to Autoregressive Conditional Duration model, what does it mean (explanation using equation will be great)?
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38 views

Analysis of irregularly sampled time series

What is the difference between irregularly sampled time series and non-linear time series? Also, what are the best methods for the analysis of irregularly sampled time series? Are there any sample ...
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How to build a function with the result of auto.arima in R?

I use: fit = auto.arima(Y, xreg=X) in R to get ARIMA(1,0,0), result as follows: ...
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wrong x axis label for time series plot of daily data [migrated]

I have 4 years of historical daily data. I plotted time series with command plot() and put xaxt="n" to customize the x axis. If ...
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63 views

Counterintuitive result when comparing two groups of time series

I have two groups of time series and I am testing the hypothesis that the groups can be distinguished in some way. Each time series is measurements of an individual’s pupil size as they listen to an ...
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56 views

Understanding $O_p$

One thing I feel like I have never mastered is the concept of $O_p$ convergence and how to use it. I understand the basic idea and what bounded in probability means, but I always have a hard time ...
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46 views

Filtering of time series

I would like information (references) about the reason why time series should be filtered before being used in a VAR model. Thank you in advance, Nikos.
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Autocovariance of an AR(3) process

I am given a general equation of an AR(3) process : $Y_t\:=\:e_t\:+\:\Phi _1\:Y_{t-1}+\:\Phi _2Y_{t-2}\:\:+\:\Phi _3Y_{t-3}$ I want to find the $\gamma _0$ of the AR(3) process but I am not too sure ...
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cointegration analysis for different level stationary series

I have a data set of of three variables: imports, exports and GDP. The import variable is I(1), but the export variable is I(1) only for constant and constant and trend but not for none. Similarly, ...
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what is 1-step ahead prediction for this AR(2) model?

AR(2) model : rt= 1.2rt-1 - 0.35 rt-2 +at, Var(at)=16 Suppose that r300 = 7, r299=5, and r298=6 What is the 1-step ahead prediction of r301 at the forecast origin T=300? Compute the variance of ...
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27 views

How much training data is enough for seasonal time series forecast

I am new to times series forecast. If I have data(single variable and timestamp) with double seasonality periods, which are 288 and 1056. And I use tbats in R to build time series data and then ...
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28 views

HMM: class residience time from time series

I'm a newbie of the statistica subject. I've seen that HMM could be used in order to model state and state transitions for time series and, since I only know that in Markov Models I could state the ...
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43 views

Using 2 sample T test in time series data

I have two data series (not stationary) and I would like to see if the mean of series 1 is significantly different when a certain condition (on the other series) is met. The theory is that when ...
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34 views

Can I remove seasonality from a cross-correlation using LOESS?

I’m attempting to determine if relationships between two abiotic variables: river discharge (flow; $m^3/s^{-1}$) , temperature ($^oC$) and a response: juvenile fish biomass ($g/m^2$) have any ...
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36 views

Probability distribution of time series

I am unable to understand concepts related to the probability distribution of binary time series. This is from the book Binary time series by Benjamin Kedem, vol 52 Let $X_t$, t =0,1,... be a binary ...
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linear regression on future values of ARMA process

We consider a stationary process $X_{t}$ $X_t - \frac{1}{2}X_{t-1}=\varepsilon_t - \frac{1}{4}\varepsilon_{t-1}$ $\varepsilon_t$ is a white noise with variance $\sigma^2$ How to compute ...
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58 views

how to use arima to do mean model

I am learning arima by this site: http://people.duke.edu/~rnau/411home.htm and I want to get the same result as following notes: ...
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14 views

Maximum Lag Length in Granger Causality Test for intraday ,1 minute, time series?

I have 2 time series having 1950 observations each. The time series represent intraday, 1 minute, close prices of stocks. Those 1950 observations cover period of 5 trading days, meaning that each ...
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prediction of variable in the future?

I have some data from sensors in my phone.I have their respective battery levels at each timestamp the sensor readings were recorded in phone.My aim is to be able to predict, lets say that i have ...
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Why are econometric analyses valid when the subject of study is inherently different?

I am reading numerous articles pertaining to unemployment as references for my own work. Yet I've encountered many where they use long time series in countries which have had some sort of pertinent ...
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39 views

Seeking basic advice re. contingency matrix for time-limited predictions

I am looking for advice on how to construct a contingency matrix ... A subject is measured on day 1 and a score is computed. This is repeated daily generating a series of scores. If on a given day ...
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30 views

Vector autoregression with interval lag terms in R?

I'd like to perform vector autoregression on a two variable system. I know that the signals $x$ and $y$ have a time lag of > 100 time points, and thus any fit with that many time lag parameters is ...
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Simple Time Series Analysis

Suppose we have collected a set of data points $\{a_{t}\}$ at time $t = 1, 2, ..., t', ..., n$. Each data point consists of the following attributes: ...
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Testing Contemporaneous Correlation

Suppose I have the following time series: ...
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How can I make sure that an LDA implementation works?

I am currently experimenting with neural nets for classification of on-line handwritten data (hence: not pixels, but time series data). To do so, I use several toolkits (internal development of my ...
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138 views

very high frequency time series analysis (seconds) and Forecasting (Python/R)

I have high frequency data (observations separated by seconds), which I'd like to analyse and eventually forecast short-term periods (1/5/10/15/60 min ahead) using ARIMA models. My whole data set is ...
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19 views

How to simulate a structural break time series? [migrated]

I want to know how to simulate the following structural break autoregressive time series: $\begin{cases} Y_t = 0.9Y_{t-1}+\epsilon_t & \text{for }1\le t< 50\\ Y_t = ...
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23 views

relationships between 3 variables

I have 3 data sets. one is the water level of a lake at 15min intervals, one is the water level of a pond next to the lake (also at 15min intervals) and one is the wind speed over both the lake and ...
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Using dates in R for Theil-Sen [migrated]

I am trying to use dates as my X variable in a Theil-Sen slope estimation and I am having difficulty using the R package zyp ...
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Identifiability in linear regression and time series

The multivariate linear regression model is given by $\mathbf{y} = \mathbf{X}\boldsymbol{\beta} + \boldsymbol{\epsilon}$, where $\boldsymbol{\epsilon} \sim \mathcal{N}(\mathbf{0, ...
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How to determine the correlation between data sets with the same period but different sample rates?

I am trying to determine the correlation between two sets of data points which span the same time period (20 minutes) but have different resolutions. The first set was recorded at 1-minute intervals, ...
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20 views

How to validate a lognormal random walk for time series data

I am currently working on a project where I need to simulate the prices of a set of $D$ substitutable commodities over time. I was hoping to do this using the following $D$-dimensional lognormal ...
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33 views

The likelihood that a time series is generated by certain ARMA(p,q) ?

I have a group ( only 20 of them, each one has 170 time pointers) of time series that I can consider as "GOOD", meaning, they have consistent statistical characteristics. I am not sure how they are ...
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9 views

Discovering dis-associations between periods of time-series

I'm interested in discovering some kind of dis-associations between the periods of a time series based on its data e.g. find some (unknown number of) periods where the data is not similar with the ...
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10 views

Are there free APIs for searching news articles that I can use to collect trend data in news coverage? [migrated]

I am working on a data-visualization web application that looks at trends in American news media coverage over time. It takes a keyword (or keywords), a date range, and a time increment as parameters ...
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34 views

How to analyze personal time series

I have a time series data of multiple subjects' performance over the time as well as time series metric of their mouse movement. In other words, for every subject, there are two graphs: Performance ...
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Factor analysis using “outliers-only” time series

Some background I run a factor analysis of a time series $Y$ using a standard OLS model with n+1 independent variables $(F,X_1...X_n)$, where $F$ is the main factor (from an explanatory power ...
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59 views

Cointegrated Vector ARMA (CVARMA) Model vs. Dynamic Factor Model (DFM)

Two questions regarding the equivalence (or lack thereof) of vector error correction model (VECM) cointegrated vector ARMA model (CVARMA) and dynamic factor model (DFM): Can every VECM CVARMA be ...
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184 views

Pattern recognition with time series analysis

I'm looking for some good pointers to pattern recognition with time series. Possibly something practical that can be easily understood. As a toy example, think about collecting data from an ...
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21 views

Discriminating for early detection of problems

I could (please) use some suggestions on how to tackle an issue that has been brought up where I work. When a new product is launched, our company tracks how many AND what type of replacement parts ...
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How does one adjust for data snooping when using ACF and PACF?

ACF and PACF are routinely used for approximate identification of a time series model, e.g. as described here. Say, one takes a look at the plots and guesses that it's something like ...
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36 views

How to interpret ACF and PACF plots

I just want to check that I am interpreting the ACF and PACF plots correctly: The data corresponds to the errors generated between the actual data points and the estimates generated using an ...
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21 views

If I am comparing actual data vs. forecasted data, is the Durbin-Watson statistic useful?

We are comparing our forecast vs actual data from the same time period and was using the mann-whitney test to help provide evidence our samples were not different. Someone challenged us saying the ...
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How to combine short term and long term time series?

I need to combine two traffic data series which are long term ( with 15 S / 30 S/1 minute interval) and short term( with 2 S/ 3 s) for my research purpose. These two types of data series reflect ...
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updating a forecasting model including the new observed data with the historical data

I want to have a one week ahead forecast for my data which includes a four years of daily historic data (three years are used as train set and the 4th year is used as the test set). I can use three ...
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Ensemble in stochastic process

I am learning a time series and forecasting course.In the book "The Analysis of Time Series by Chris Chatfield" it says that We only have single outcome of the process and a single observation on ...