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

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Predicting modem failures a day in advance

I have a time series data set of performance data from thousands of individual modems. Each modem is probed and gets a new entry in the database every 15 minutes. I have 100 days worth of data like ...
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30 views

Is there any way to account for variable interaction in R's auto.arima?

I'm using the auto.arima function in R's forecast package to build an ARIMA model with external regressors. I have a ...
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22 views

Simulation of time series from pdf function, defined for each time step, with aucorrelation

I have a model defined by $\mathbf{X}= (X_{1}, X_{2},... X_{t} ... X_{M})$, where for each $t$ (time step) $X_{t}$ follow a distribution ${D(\alpha_{t}, \beta_{t} )}$. I want to generate time series ...
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40 views

How to test if a time series becomes stationary?

I am new to time-series analysis, but I am dealing with a non-seasonal time series data now. The plot of the data looks like the following, so there might be huge variance at the beginning, and ...
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14 views

Sample Size correction for Times Series

I have weekly time series data time Jan1-Jan7 Jan8-Jan14 Jan15-Jan22 . . . Dec17-Dec23 Dec24-Dec30 Each week there is sample of the total number of people who ...
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39 views

How to parameterize coefficient matrix to restrict eigenvalues?

Consider the $r-$dimensional autoregression $$ y_t = Ay_{t-1} + v_t, v_t \overset{iid}{\sim}N(0,\Sigma). $$ It is well known that if all eigenvalues of $A$ have modulus less than unity then this ...
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92 views

Keras - Predictive ANN model converging on a single value. Overfitting?

I'm training an LSTM (using the Keras python library) to generate sequences. My X training data is a list of sequences, and the Y training data is a list of the final values of those sequences. The ...
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2answers
63 views

Trend and Breakout detection in time series

I am working on several types of system metrics which characterizes several components of an application. The metrics range from system metrics like cpu.utilization to network metrics and database ...
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32 views

How to forecast with a regression model with ARIMA errors?

I have obtained the following coefficients after using the auto.arima function in R: $y_t = 0.87 x_t - 0.51x_{t-1} + n_t$ where $n_t = 0.83n_{t-1} + e_t$ My question is, how to obtain ...
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1answer
36 views

VAR - ARCH LM Test results are conflicting

I'm using the R package vars to model multivariate series with VAR of order p = 5. The multivariate series is: $$ Y_t = ...
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15 views

I can't correct the OLS model with heteroskedasticity by the lmtest means

i'm using a selvaggio model to explain the behavior of deposits in a bank's data, and i need to use the estimated parameters, the problem is the heteroskedasticity that i detectect with breusch-pagan ...
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Statiscal test for ranking time series based on change points and values

I have five time series, each of which consisting of 30 measurements (pressure) from sensors (on three machines located at five different locations). I would like to rank those time series. I run a ...
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36 views

Surrogate Time Series using Fourier Transform

In the Surrogate Time Series (Schreiber, Schmitz) paper, the authors claim that surrogates for a second order stationary time series can be generated by taking the Fourier Transform of the series, ...
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17 views

Why is the periodogram of differenced white noise not flat?

I'm a final year undergrad who was doing a project that involved the implementation of a frequency-domain volatility estimator. I haven't a lot of stats background so not understanding a point that ...
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21 views

Inclusion of exogenous variables and prediction of TVAR models (tsDyn package in R)

I'm trying to use the function TVAR from tsDyn package in R, but I'm having problems in including exogenous variables. Also, I still haven't found a way to predict ...
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61 views

Testing differences between two experimental groups involving time series data

I am trying to apply a statistical test to data in my science fair project. I'm looking for suggestions on which test I should use. The graph is shown below the text. I am studying the effect of a ...
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1answer
32 views

Marginal vs. conditional models of vector autoregression (VAR)

I have a vector autoregression, VAR(1). All random variables are weakly stationary and our white noises are all iid: ...
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14 views

MATLAB regression showing 'overparametrized' error

So, I'm looking at the time series of earth surface temperatures from 1880 to 2015, a total of 1632 data points (Monthly Data). I was trying to find the trend using a polynomial fit. This is what I've ...
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14 views

How to compare two time series data from two different models for a same variable?

I am working on the isotopic value of Evapotranspiration, an environmental variable. There are two models to compute this value, so I am planning to use these two models to compute the same variable. ...
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1answer
26 views

Identification of i.i.d. series

I have a time series $$ X(t+1)= X(t) $$ or $$ X(t+1)= 1-X(t) $$ with equal probability and $X$ has a uniform$(0,1)$ distribution. Is the series i.i.d.?
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21 views

How do I detrend this (non-linear) time series before differencing?

I have a variable that looks like this (after taking natural log): I can't run stationarity tests as there are clearly structural changes in the data. How can I get around this – am I supposed to ...
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61 views

Difference between VAR vs SVAR

I've problem with the difference between the VAR and the structural VAR. I've read books and articles but I don'get the difference between these two since we use lower triangular matrix when imposing ...
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23 views

How can I use inputs of lower frequencies to predict an output of higher frequency?

I would like to use a NARX or a LSTM to use different type of data at different frequencies -for instance weekly, monthly and quarterly- to predict data sampled at a higher frequency -in my case, ...
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1answer
67 views

How to check if a series increases or decreases?

I work with Google Adwords. Recently Google has changed its layout regarding its ads. And I want to measure what was the impact of that change. I don´t want to do a super analysis, but I would like ...
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21 views

python statsmodels: fixing ARIMA lag parameters (non-consecutive lags)

Is it possible to use non-consecutive lags in statsmodels' ARIMA? i.e. using daily lag coeficients in my hourly dataset: $y(t) = \beta_0 + \beta_1y(t-24) + \beta_2y(t-48) + \ldots$ It seems like you ...
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1answer
23 views

Designing a training set for regression on probabiltiy values given time , categorical and continous features

Assume we have following variables out of which "Probability of sale " needs to be predicted , and this is to be done for a portable business vendor whose location changes with time : Business ...
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14 views

ARMA stationarity conditions

Are ARMA(p,q) model stationarity conditions are the same as for AR(p) or some additional requirements must be met?
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45 views

Python statsmodels ARIMA ValueErrors

I am using the statsmodels package in python to generate a set of ARIMA models for a series of log returns multiplied by 1000. I am iterating through possible models (p, d, q) starting from (1, 0, 0) ...
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29 views

Anova to compare trends in time series

I would like a test to compare the trends of multiple time series. I have already saw others solutions, like fitting a same arima model and compare both with a f-test but I want to try another one. ...
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1answer
63 views

Forecasting Poisson, accuracy and prediction intervals

I'm trying to forecast Poisson data, divided in groups, of 1-26 months of data, depending on the group. Of the pooled data ...
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27 views

What is $\hat{\sigma}^2$ for AR(1) non-causal case?

Assume that $|\phi|>1$ and {$X_k$} is the stationary solution of the non-causal AR(1) equations, $$X_k=\phi X_{k-1}+Z_k$$ where {$Z_k$} is white noise with mean $0$ and variance $\sigma^2$. Show ...
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24 views

Get most occurring value on a graph

I have a data series which is continuous (there is data in between individual data points not captured by the series). There are many inflection points within the series and my goal is to find 5 most ...
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55 views

What to do if time series data remains autocorrelated?

Data: I have 92 years of monthly climate data. One of my variables is a drought index (SPEI) ranging from -2 (dry) to 2 (wet). All the data can be found here. Data Structure: ...
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33 views

How to interpret output from forecast package

The forecast package has the function auto.arima and forecast to model time-series. ...
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28 views

I want to make a Logit regression with lagged explanatory variables - but differenced

First of all a little information on my thesis. We are trying to analyze which hedging strategies yielded the highest cash flows when exchanging USD to EUR. To do this we priced all strategies ...
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0answers
21 views

Survival (Kaplan Meier) of signal transmission that can both fail and recover

I'm investigating the failure to transmit of a number of signals in time. In my data I often see signals transmitting for quite a long time, but after some time they gradually start failing but still ...
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10 views

Comparing months across years (e.g. Jan 2014 to Jan 2015, Feb 2014 to Feb 2015, etc.)

Can anyone point me to the right statistical test for this? Our hospital calculates the % of hours each month we are on diversion (i.e. our ER is full and we can't accept transfers). There is some ...
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1answer
26 views

NA in ARIMA model, is it suggest that the model is over fit?

my professor says that if we see that there are NA values for the AR or MA terms(either the estimated values or the estimated se) in the R output for the arima models fitted using the arima() ...
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26 views

Are lags created in an auto.arima model?

My apologies in advance for asking what I suspect is a dumb question. I have looked around and I can't figure this out. I've done an auto.arima model in r. ...
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Covariance between added harmonic timeseries

I am trying to construct a covariance matrix for an optimization between two added harmonic time series. In general, the basic equation looks like this: $Z(t)=Y(t)-X(t)$ When I break this down into ...
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optim() convergence in fitting gamma distribution to separate peaks of time series data

Trying to fit gamma distribution to each separate peak of time series data (chromatography). As a peak i take local minimum-maximum-minimum part of the data each time. Since the peaks values do not ...
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27 views

Granger causality and Wald test in multivariate non-stationary case

I have a list of market indices (like 20 indices) and want to analyse which indices are the most important for prediction of CDS of a company. Most of the time series are I(1) processes. I was using ...
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Stationary time series with outliers

Does anyone have stationary time series data with some outliers from real life? I'd like to try my robust estimation method. Thank you!
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how to create baseline and forecast time series data

I am a statistics newbie and I have daily time series data for the last 5 years. The csv has two columns date and website session_count. To create a baseline, do you generally just take the average ...
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1answer
57 views

Start up values for the Kalman filter

I am trying to understand how the start up values (initialisation) are calculated in the Kalman filter. As an example, I simulated the MA(2) model below. ...
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12 views

Bad error measurements with forecasting Poisson distribution

I have pooled data the last 26 months of a Poisson distribution on which I want to forecast. There's neither a trend nor seasonality in the data so I need to forecast with a stationairy model. I ...
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1answer
36 views

Time Series Prediction for process plant

Firstly, we have no knowledge about advanced data analysis or data mining. We are working with process plant which gather data that comes into the process plant. We use sensors data for the input to ...
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Graphing number of new patients

If you have counts of new patients over two years, counted at the end of every quarter (Jan-March, so counted on March 31 - total number of new patients in that quarter) - would you use a line graph, ...
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22 views

Building a time series model on Website login timestamps

If I have to build a time series prediction model and all I have is a sequence of timestamps of a user when he logs in to a site, how do you model that?. Here is the first few rows of the data. I ...