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

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Estimate global mean and stdev from samples taken at regular intervals

I have data from a load test of an automated system with several thousand data points that cover roughly 1 week of operation. I need to compare several algorithms for this system to see which is ...
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426 views

Calculating the likelihood of time series data when there are missing data

I am trying to calculate the log-likelihood of some time series data given parameter sets estimated in BUGS. I can not figure out how to handle some missing values at random points in time. For the ...
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2k views

Formula for one-sided Hodrick-Prescott filter

I am not very familiar with filters. The Hodrick-Prescott filter as one can find it e.g. in wikipedia is two-sided. I also found an R implementation for this in the R package mFilter. There the filter ...
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1answer
587 views

Comparing means of two simple time series

I'm trying to look for difference in timing (ie. earlier/later) in a variable measured at regular intervals between two groups. This seems like a simple experimental design, and working in R, I'm ...
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255 views

Time-series stationarity

If I difference a time series and take out trend and seasonality ... does it mean we are left with only irregularity on which we plot the acf and pacf to arrive at the MA and AR order? Do 1st ...
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4k views

Two seasonal periods in ARIMA using R

I'm currently using R to predict a time series with these instructions: ...
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1answer
451 views

How to test for serial correlation of a time series itself (not residuals)?

We know that Ljung-Box test can be used to test for the residuals of a fitted model. But to test for the serial correlation of a time series itself, is there a way to do that?
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2answers
561 views

What's a stationary VAR?

What is a stationary VAR (vector autoregression)? Can a VAR with non-stationary variables be stationary? How do you test whether a VAR is stationary or non-stationary? (Example in ...
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1answer
177 views

How can I get annual rates of change for combined trend estimates?

I would like to combine trend indices (gained with different methods referring to the same subject, assuming they do not differ significantly) of two different time series and to derive the combined ...
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625 views

Preliminary estimates of ARIMA in R?

We know that dealing with model involving MA factors is not easy to estimate, since there are past values of errors to be computed recursively. And this recursive estimation requires preliminary ...
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502 views

Johansen's $\Pi$ is full rank except variables are non-stationary

I have two variables. They're both $I(1)$ even when I fit constant and trend terms into the ADF test. The $p$-values for the stationarity tests are around 0.5 so it's not a marginal case. However, ...
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27 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 ...
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744 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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189 views

samples from forecasts of VAR time series model in R

I'm trying to do a power analysis for a future experiment with time series financial data. We'll be splitting the data by random (actually, stratified) geographies, so we have a control and ...
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319 views

Correlated time-series

First, I would like to apology if my vocabulary is not correct. I am not statistician (and not mother tongue English speaker either). So here is my problem : For n subjects I got 8 values (human ...
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1answer
562 views

How to calculate this formula for variance?

I have a function which I would like to use Taylor expansion and calculate its variance by the following formula: The formula for variance then becomes \begin{align} ...
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1answer
528 views

How to regress a time series of proportions?

Every month, an organization surveys some of its customers (the total number of customers is also known). The sampled customers answer a survey with a dozen or so questions; sometimes, customers ...
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6k views

Using the R forecast package with missing values and/or irregular time series

I am impressed by the R forecast package, as well as e.g. the zoo package for irregular time series and interpolation of missing ...
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336 views

Any alternatives for plotting (long) time series?

I'm looking for ways to visualize large time-series other then in traditional 2-axis line charts. More specifically, I hope to find a way that intuitively reveals patterns in the data such as the ...
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272 views

Hypothesis testing for two data series

I am currently pursuing research in management, but I have a serious problem with selecting the right statistical method. I have quarterly data for a couple of financial ratios (for example Return ...
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60 views

Confusion related to modelling of temporal correlation

I was a bit confused about the modelling of temporal correlation in a certain paper. Lets say, I have vector $\bf{x}$ of dimension m, and a time series $\bf{x_1},\bf{x_2},...\bf{x_N}$. Now I want to ...
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179 views

Bayesian Forecast with Minimal data

The following very simple forecast has been very helpful to me in applying basic methods.. and I have read that Bayesian methods may be superior for small data forecasting but I have not seen any ...
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1answer
7k views

Example of time series prediction using neural networks in R

Anyone's got a quick short educational example how to use neural networks (nnet in R for example) for the purpose of prediction? Here is an example, in R, of a ...
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1answer
124 views

Research Methodology on Fareless Bus System

I am working on a project for a Masters Project. The town I am looking at Switched to a Fareless system in Feb 1, 2011. I want to look and see if this increased ridership by a substantial amount. I ...
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300 views

How to forecast number of donations?

I am trying to forecast/predict the number of donations expected to be received at multiple locations across the country. I have and want to use the information I have. This information covers the ...
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117 views

Hypothesis tests on 2-dimensional panel data w/ 1 characteristic?

I have a 2-dimensional panel data set with one characteristic looking along these lines: ...
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116 views

How to test for integrated order 2/non-stationary I(2)?

How do I apply the Augmented Dickey-Fuller (or alternative) test to determine if a variable is $I(2)$ instead of $I(1)$? Is there functionality for this in R ...
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367 views

Difference between unrestricted VECM and restricted VECM?

What's the difference between an unrestricted and a restricted VECM? I believe a hint lies within the cajorls()[1] function of R language's ...
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3answers
355 views

Putting stationary variables through Johansen procedure

Is it okay to feed $I(0)$ variables into the Johansen procedure? I've read three sources that seem to state that this is not what you're supposed to do. However, whenever I've done this, I notice that ...
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160 views

Comparing strength of trend and seasonality for various levels of aggregation

I have a monthly time-series for which I've fitted the time-series regression model including linear trend and 11 dummy variables for seasonality. Then, I aggregated the original time-series to ...
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27 views

Correlation of a poll and another measure

I have this problem and I'd like some pointers to a "standard" method of solving this issue. I have two time series, with points taken at the same time for each one of them; series A is a poll, of ...
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1answer
1k views

Multicollinearity in OLS

I am reading Greene's textbook Econometric Analysis where he says that, if there's multicollinearity, then: Small changes in data lead to large swings in parameter estimates. Coefficients have high ...
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104 views

Assumptions for Hurst exponent calculation

Are there any general assumptions for the calculation of the Hurst exponent? Does the signal need to be stationary, for example? Does it depend on the method? What about the length of the time ...
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158 views

How to assess stability of daily time series in sentiment analysis?

I developed a measure of "sentiment" and I have time based data and used the measure to derive a daily sentiment time series. I am looking for some way to establish reliability or maybe stability. For ...
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83 views

Dealing with dependant data when estimating probability of an event happening

I have 10 years worth of data from 1970 to 1980 (40 quarters). For each quarter I have five measurements M1, M2, M3, M4 and M5. TWIST: Although the data I have is on individual patient level, the ...
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211 views

Time series regression - ML estimation

I have a linear regression model with some correlated errors: $Y_t=\beta_0+\beta_1X_1+\beta_2X_2+\epsilon_t$, where $\epsilon_t$ is a AR(1) i.e. $\epsilon_t=\phi\epsilon_{t-1}+\nu_t$ with $\nu_t$ as ...
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1answer
1k views

Cross-validation with neural networks yielding worse results than a standard neural network

Summary: when using a 10-fold cross-validation procedure where each training set is used to generate N bootstrap samples for processing with NNs. How do I provide my NN with correct sequence and ...
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76 views

How to generate more than two correlated series in R?

I'd like to generate more than two (i.e 3) correlated series, take an example when the series follows an IMA(1,1) process, at first I want to generate three correlated random errors ...
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2answers
604 views

Dummy interaction variables are always non-stationary?

I want to know why we can include dummy interaction terms into time series models if they're always non-stationary? For example let $X_t$ be $I(0)$, $X_t \sim N(\mu,\sigma^2)$ and $D_t \in \{0,1\}$. ...
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926 views

Time series forecasting lookback windows — sliding or growing?

Are there any good reasons to prefer a sliding model training window to a growing window in online time series forecasting (or vice versa)? I'm particularly referring to financial time series. I ...
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345 views

Smoothing a time series of ratios

I have a time series of proportions, $x_t = \frac{a_t}{b_t}$ i.e. $x_1 = 2 / 30, x_2 = 1/10$, ... I want to smooth $x_t$. Should I apply a smoothing function directly to $x_t$, or should I smooth ...
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180 views

How can I measure the effects certain events have on the frequency of other events over time?

EDIT: added more details following @kjetil comments I have the following problem: I monitor one stream of events of type A - those events can be considered instantaneous. I also monitor additional ...
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326 views

How to chose optimal number of lags and inputs?

I'm using Genetic Algorithms to do inputs selection in a time series problem. The issue is that the number of possible inputs is very large (100 possible inputs + inputs' lags) and I don't know a ...
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267 views

Generalized least squares with insignificant predictor variable

Suppose I have fitted an standard linear regression mode $Y=\beta_0+\beta_1X_1+\beta_2X_2+\beta_3X_3+\epsilon$. Based on the ACF plot or PACF plot of the residuals for this regreesion model, I found ...
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1answer
668 views

Conditional model using function tslm in R package forecast

I would like to use tslm with data that has intraday seasonality and a different pattern on business days and on non-business days. If data.ts is my time series then I would like to use something like ...
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26 views

Mass to area to mass/min

Given an collection of mass values (in $g$) which are samples collected over a minute in a moving-window fashion (thus their sum represents the mass per minute observed in the system), and a formula ...
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1answer
95 views

What is the distribution that can properly describe the PE fluctuation of a stock

I have observed the historical PE (price / profit) value of a stock and realized that it roughly follows a log normal distribution. However, even when the next earning data point is easily ...
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0answers
305 views

Correlation of non-uniform time-series data?

I have two datasets of time-series data, each with arbitrary, non-linear sampling intervals. I'm planning to analyze them using either Pearson or Spearman correlation (determined by the detection of ...
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0answers
78 views

How to compute variance of a continuous time sequence?

I am observing two continuous time-series where at every instant in time I may observe a unary event. That is, for each sequence, say $S_1$, I have a data set comprised of $S_1 = (t_0, t_1, ..., t_m)$ ...
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243 views

Identifying periods of non random behavior in time series

Im looking for some pointers on which topics I should be looking into in order to identify periods (of non fixed length) which deviate from randomness. I have a feeling hypothesis testing may be what ...