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

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Representation of ARMA processes

Question Consider the following process: $$2y_t-3y_{t-1}+y_{t-2}=\epsilon_t-\theta\epsilon_{t-1}$$ What is the model for the process $w_t=\Delta y_t = y_t-y_{t-1}$? Attempt I have solved the ...
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Comparison of Time Series Data

I'm new here, and fairly new to statistics, so I apologize if this is an easy question, but I'm stumped. I'm doing a research project simply for fun (yes, I'm weird like that). I was never able to ...
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Detecting time-shifted time series

Assume there are two time series of real values. How to test hypothesis, that these series are quite the same, but there is a time shift between them? Sorry, if the question is too basic. Thanks in ...
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“Explaining” a time series - conceptual explanation needed

Imagine I have a time series for an animal population and a time series for a climatic variable during the same time period and at the same location. Unfortunately the data are observational (i.e., no ...
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25 views

Temporal Correlation in R

Having used stack overflow for years without signing up I now truly need some help! My data consists of samples collected from the same location in three different streams between 2012-2014. The data ...
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44 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
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Neural net model - error during training

I'm getting started with R, I really like it but recently I found myself in a corner. I'd like to build neural network model that predicts heat consumption. I have historical data that contains ...
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44 views

What is the difference between forecasting based on ARIMA and logistic curve? R

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product. This is what my database ...
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17 views

Test to compare an effect on a variable on a daily basis

I would like to know the effect of an external factor on the number of visits on a website during a period of 4 weeks (only search visits from Google). For this, I measured the number of visits every ...
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14 views

Nonparametric Time Series Forecasting

I am trying to understand how Kernel Density Estimation (KDE) or (nonparametric) Quantile Regression can be used to forecast values given historical observations. For example, consider the following ...
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47 views

My fixed effect model and methodology

I'm doing my master thesis on FDI effect on Chinese wage inequality. I am new to quantitative econometrics so I have no idea if my wage equation is correct. $$W_{it} = β X_{it} + λ_t + η_i + ε_{it}$$ ...
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Is ARIMA model appropriate for this dental research?

Please, I have a doubt in my study for doctoral thesis… Title: “Development of a thermal cycling protocol for dental materials”. Objective: to create a protocol for thermal aging, from measurements ...
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8 views

Significant difference real or due to the internal variability?

In my data I have 9 different sets of data for 2 different groups. Each one of these datasets is the same measurement changing over the time. If I make a graph, I can see 9 lines for each group. I did ...
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65 views

Forecasting with holiday dummy variables

I have an example of call center data for 2013. There are 261 days of data (excluding weekends). For 2013, I have included a holiday dummy variable (holiday) for ...
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38 views

What does “AR(p) filtered series” mean?

I guess this means that omitting some variables in a certain interval, say, $(x_1, x_2, x_3, x_4, x_5) \to (x_1, x_5)$ in AR(4) model. Is it right? Or does this means eliminating autocorrelations ...
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41 views

The effect of ommission of relevant variable in the regression model on adjusted $R^2$

Let's say I have two regression models (I) $y_t=\beta_1+\beta_2 x_2+u_t$ (II) $y_t=\beta_1+\beta_2 x_2+\beta_3 x_3 + u_t$ How the omission of relevant variable (not irrelevant variable) affects ...
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Should plots for time series use a logarithmic scale for duration/time?

I was reading this tutorial on ggplot2 and was struck by a bit where it said that durations are typically best displayed along a logarithmic scale Is this an ...
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ISPSS: Cross-sectional time series analysis

I am trying to run a multiple regression in SPSS. I am using panel data with 4 independent variables. Of these, one is a dummy variable. Can someone please guide me through the process or give me ...
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What I have to undergo testing before proceeding to time series analysis? and after?

I have to conduct a time series regression analysis. Before proceeding I tested for stationarity and I verified that the variables are distributed according to the normal probability distribution. ...
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15 views

Wavelets with forecast model

I am new to wavelets decomposition technique and am trying to use it with time series model. What I use now is that use discrete wavelet transform. I use Daubechies with 4 as mother wavelet with ...
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12 views

Measuring the standard deviation in Pattern recognition

Sometimes in pattern recognition say Character recognition, Hamming distance is used although there are other distance measures. But if the pattern is represented in (1,0,-1) then Hamming distance is ...
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2answers
47 views

Similarity measures for point processes

I have multiple measurements of a point process: vectors of 0's and 1's. I'm trying to gauge the similarity of the measurements, but have no idea how to proceed. Any suggestions? Thanks!
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144 views

Differencing a time series

I am looking to find the ACF of a time series, but after it is differenced. $y_t = a_1y_{t-1} + \epsilon_t , \mid a_1 \mid < 1$ I understand that to find the ACF this process needs to be ...
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76 views

Clear steps to calculate coherence between two time series

I originally posted this on stackoverflow.com and then deleted it and moved it here My question is similar to Similarity of two discrete fourier tranforms (specifically the selected answer). I've ...
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23 views

Literature for prediction models where each training example has a different amount of data?

This could be a machine learning question as much as a statistics question, but I think this is the best place to put the question. Here are three different examples of problems where each ...
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Which arma model is best one?

I am studying ARMA models. ARMA(25,25) or ARMA(1,1) which one better model? Why? I think that the reason is the ommission of irrelevant variable
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How to Build a Foresight System?

For a research project, I'm asked to find ways to build an economic foresight system. For example, for the production of cheese. We will have data about the market indicators, like price, demand etc. ...
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Testing for a drop in bookings

We're developing real-time alerts for fine-grained (every 5 minutes) time series bookings data, and I'm looking for the best approach to doing this. Idea is that if over the past 10–15 minutes (say) ...
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14 views

Pseudoinverse for time series filtering

Suppose I have a few time series, that are strongly correlated to each other, and I consider this to be noisy data. How do I use the pseudoinverse technique from image processing to filter this data?
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32 views

How to analyze healing time when the follow up times are not equal and we are looking at a specific time?

I would really appreciate if you could help me with your expertise: I have a study in which I evaluate patients for healing after discharge. So I have two group, healed and non-healed patients. The ...
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AR(2) simulation problem

Take covariances $Cov[X_{t-2},X_{t}]$, $Cov[X_{t-1},X_{t}]$ and $Cov[X_t,X_t]=Var[X_t]$ and calculate the parameters for the AR(2) process ($a_1$, $a_2$ and $\sigma^2$ (the variance of the error ...
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Interpolation of time series data

I am working on using cubic spline interpolation in time series data. I used Galdolfo and Prachowney algorithms. Now how do I obtain estimates of models of cubic spline?
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Special method for forecasting on time-series clusters in R?

I'm doing a project related to identifying sales dynamics. My database contains 26 weeks after launching the product (so 26 time-series observations equally spaced in time). I used two methods ...
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How to model to improve the room usage efficiency based on motion sensor history

To reduce the confusion, I changed my application from traffic to meeting room, so this application is about modeling a meeting room efficiency , the data collection is built by placing a kind of ...
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How can I smooth noisy time series data to explore possible relationships

First CV post but prior S.O. user. Thanks for your patience as 'stats' is not my natural habitat. I have data in the following form, in which I am trying to see if there is a relationship. Daily ...
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42 views

How to find which time series is trending more?

Let us say I have two sets of time varying series as shown below: ...
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How to interpret the characteristic roots of moment equation of a AR(2) model?

I am learning the financial time series using the book 'Analysis of financial time series' by Ruey Tsay. In chapter 2, they introduced AR(2) models. The moment equation (which is the function between ...
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Detection of periodic patterns using DWT

Is it possible to detect a periodic pattern in a time series using discrete Wavelet Transform? Is there any package in R to do this job?
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Statistical models that incorporate factors stepwise?

I am working on a dataset in R that essentially follows 20 groups of individual organisms through time. I am interested in assessing what factors impact their mortality. I have 5 factors that I have ...
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Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
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Developing an appropriate time series model to predict sales based on past month record

I have been operating an online business for two years in a row now, so I have my monthly sales data for about two years. My business for every month is certainly affected by seasonal swing ( performs ...
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Interpreting a PCA Biplot of a time series?

I had a question in regards to PCA with times series data, and specifically how to possibly interpret it. Normally, PCA is used by other software that I use in relation to de-noising a data set by ...
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Plotting a timeseries in R as stacked bar [migrated]

I have a dataset that look like the following | SUBJECT | ACTION | DURATION | |---------|--------|----------| | 1 | A | 39,57 | | 1 | B | 1,48 | | 1 | B | ...
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High Ljung-Box p-values at large lags

I am trying fit an ARIMA model to stock returns. I have reached a decent model using the AIC criterion. However, the ljung-box p value under a diagnostic plots are pretty weird. The null ...
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269 views

Improving a linear regression: Add predictors or change model?

I am trying to model a time series variable $Y_{t}$ with $4$ physical predictor variables. I used the following linear regression: ...
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16 views

What time series models capture acceleration?

Suppose I want to test whether or not a time-series gains more momentum if it is accelerating, what sort of time series model would I need to model that? Would it be captured by the moving-average ...
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57 views

time series is obviously periodic, but seasonal decomposition is not working in R

my time series is obviously periodic, but the seasonal decomposition using stl() is not working in R: ...
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Linear Mixed Models with variable time points in SPSS

I am analyzing a clinical study measuring patients' symptoms and brain structure sizes over three time points. The "visits" should be at baseline, 3 months and 12 months but they vary considerably and ...
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Constant forecasts in SPSS

I have weekly data for the last four years. I am using SPSS to do forecasting. I am getting a constant value in the forecast period. What could be the reason behind it? Is it due to defining weekly ...
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What is the autocorrelation function of a time series arising from computing a moving standard deviation?

Say I have a time series of observations and I compute a measure of the variance of that time series as the standard deviation (SD) in a rolling window of width $w$ and that window is moved in single ...