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

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How do I quantify the decay in the initial condition of an AR process?

I'm working on basic code that generates data from AR and VAR processes; the code generates enough observations to dampen the effect of the initial conditions. For example, if I want to generate 30 ...
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30 views

Sales prediciton [on hold]

what kind of prediction would be most suitable to approach having a dataset like this? ...
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5 views

Specifying complicated hierarchy in hierarchical time series data

I have a hierarchy in my time series which looks like follows (attached the image, sorry for a bad image). How to construct the hierarchy and do reconcilations in such cases? Can someone please help. ...
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16 views

Conceptual doubt in prediction intervals in time series forecasts

Background: In the second chapter of Dr. Hyndmans book on Forecasting, he mentions the use of prediction intervals to define a range of possible values demand can take in a future interval. The ...
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21 views

Variance of predictors in Regression affecting the results

I posted this as part of another post, but got no answer, so am re-posting as a stand-alone question. In a time series regression model I am finding the log differences of a predictor (currency rates) ...
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0answers
25 views

AIC - different values based on different R functions

I am a beginner in the whole forecasting/regression/time-series topic. While reading "Forecasting: principles and practice" from Rob J Hyndman and George Athana­sopou­los i found something strange. ...
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1answer
16 views

IRFs and cumulative IRFs

This is just a quick question about IRFs and cumulative IRFs. I know that for stock returns the IRFs indicate the return effects while the accumulated IRFs indicate the price effects if my variables ...
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17 views

AR-GARCH model with r [on hold]

I will analyze time series data and I have already got the data. However, I cannot specify parameters from the data with R. I want to write R code of AR-GARCH with some factors but I cannot find the ...
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1answer
16 views

What statistical analysis is appropriate for a before and after design (where participants are not necessarily the same people)

I am trying to figure out what is the best statistical analysis for my data. I looked at two companies in timepoint 1 (baseline) and timepoint 2. Company A did an intervention, Company B did not ...
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23 views

ARIMA fitted values vs predicted values

I am unsure of how to interpret the difference between the fitted and predicted values from an ARIMA model. I purposely simulated a change-point in my data. I am comparing an ARIMA model with and ...
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1answer
65 views
+250

Interpret Regression Coefficients After various Differencing

There are few explanations I can find that describe how to interpret linear regression coefficients after differencing a time series (to eliminate a unit root). Is it just so simple that there is no ...
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1answer
46 views

Spurious regression /correlation

In a time series regression I am finding a certain predictor variable significant which should not be, according to the client. Could this be due to the higher variance that this predictor exhibits ...
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1answer
32 views

Quantification of the extent of periodicity in a time series using fractal analyses

I need metrics to quantify the extent of periodicity between of a time series (for comparison with other time series), considering the time series is almost periodic. By almost periodic I mean: if I ...
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1answer
38 views

Multidimensional time series clustering

I have unemployment rates and interest rates per country over time. I want to cluster the countries that have similar dynamics and levels in both dimensions together. What could be a reasonable ...
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0answers
16 views

What mean coefficients in autoregressive model and how calculate them?

What mean coefficients in autoregressive model and how calculate them ? yt=c+ϕ1yt−1+ϕ2yt−2+⋯+ϕpyt−p+et, ϕ1, ϕ2 ... This coefficients are "fourier transform"? Can ...
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0answers
6 views

How to use tbats model parameters from a previous execution to fit another series in R?

I trying to model a time-series using tbats from forecast package in R. I have divided the ...
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1answer
46 views

Arimax Prediction : Using Forecast Package

The arimax function in the TSA package is to my knowledge the only R package that will fit a ...
2
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1answer
28 views

Classify streaming, partially complete data into groups defined by prior clustering

Suppose I have M observation vectors, offline, $y_t$, $ t =1 ... M$, and each observation is $n$ dimensional. I then cluster these observations into $k$ clusters. For computing the clustering ...
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1answer
21 views

Correlation of motion or movement timeseries

Assuming we have tracked the movement of a group of people, is it possible to detect, if one person follows another? Or if even a group of people follows one person? To be more specific: In a crowd ...
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80 views

How to do forecasting with detection of outliers in R? - Time series analysis procedure and Method

I have monthly time series data, and would like to do forecasting with detection of outliers . This is the sample of my data set: ...
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0answers
18 views

Deep Recurrent Neural Net (RNN) implementation/toolbox in MATLAB [on hold]

Could you please advise me about any Deep Recurrent Neural Net (RNN) implementation/toolbox in MATLAB (using pre-training and fine-tuning). Thanks
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7 views

GLMMpql and GEE differences for univariate time series

I am hoping to compare a GLS, GLM, and GLM with autocorrelation for a non-normal data set using their RMSE values. I was originally intending to use a GLM-GEE, because I have seen them used in the ...
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0answers
16 views

Specifying SARIMA model parameters

In SARIMA model described by the equation $x_t=(1-L)^2y_t$, what are the $d, D$ and $s$ parameters? Is it $d=0$, $D=2$, $s=1$, or $d=2$, $D=0$ and then what can be the $s$?
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1answer
66 views

Why do sample ACF/PACF suggest different TS models after box-cox transformation?

I use auto.arima function in R to fit a TS model to a annual data composed of electricity demand. The series is twiced difference to eliminate the trend in the data. After that the data is transformed ...
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2answers
26 views

Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
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18 views

How to check stability condition of VEC estimates in R?

I am estimating a VEC model and need to check the stability of its parameters. The vars package has a function to do this on an object of class varest generated by ...
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25 views

Association analysis of different angiogenic markers with different time points [on hold]

I would like to know the statistical tests which can be used to measure the association of the angiogenic measurements, measured at five different time points, with a biomarker.
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20 views

Is there a classification model with possibility to set transition probabilities for each sample?

There are models where we can to set initial transition probabilities between classes like Markov models. But what if we need to change the probabilities dynamically depends on all previous ...
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1answer
16 views

Variance and autocorrelation with missing and/or unevenly spaced data in time series

This question concerns the general problem of working with data that might have missing and/or unevenly spaced values. Let’s call this real data. Specifically I am calculating rolling variance and ...
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9 views

General to specific approach vs information criterion

In ARDL model I want to determine proper lags for model. I have two option for this. The first is General to specific approach and deleting all insignificant variables. And the second is using ...
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12 views

Question about number of observation in Generalized ESD

According to http://www.itl.nist.gov/div898/handbook/eda/section3/eda35h3.htm The number of observation is denoted by $n-1$ Why dont we just use $n$ instead of $n-1$? Is there any special meaning ...
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24 views

Seasonal adjustment for daily/weekly data [closed]

I have daily sales data which display strong weekly seasonality as well as monthly seasonality. It means that there are spikes/dips at the end of each week and greater spikes at the end of each month. ...
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1answer
8 views

Suggest suitable time series like ML model

We have data (1901 to 2002) in this schema: Fotrnight, Temp, Precipitation, WetDayFreq, (and other env variables), Cholera_cases we have one such table for each ...
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1answer
12 views

Do I have endogeneity problem if I use overlapping observations in AR(1) model?

My dependent variable is $y_t=\frac{data_t}{data_{t-4}}-1$ with quarterly data and the model is standard AR(1): $$ y_t=\alpha_1 y_{t-1}+\beta x_t+\varepsilon_t. $$ I was told that due to ...
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1answer
61 views

How should I test for autocorrelation in this time series context?

I have data sets in which different people estimate a certain quantity. They potentially can see the estimates of anyone who participated before them, but in practice they're only likely to look at ...
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1answer
30 views

Quasi-experimental design : time series analysis

I am busy designing a medical research for my masters(epidemiology)on time series analysis, comparing the trends of Pulmonary TB bacteriologically confirmed cases before and after the introduction a ...
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13 views

Constant-output Markov chain in time-series prediction

Suppose a Markov chain with two discrete states $A$ and $B$. The probability of moving from $A$ to $B$ is $0.1$ and the probability of moving from $A$ to $A$ is $0.9$. Similarly, $B$ to $B$ has ...
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25 views

Change detection in hidden markov models

I have many questions about hidden Markov models. Let $Z_1$, $Z_2$, ..., $Z_n$ be the latent variables, and $X_1$, $X_2$, ... $X_n$ be the observed ones. Let's assume that the parameters of the ...
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35 views

How are Markov chains used for time-series forecasting?

How are Markov chains used for time-series forecasting? Since the next state depends only on the current state, I would guess that I should first find the steady-state probabilities. To predict a ...
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5 views

Time-series variable normalization before using state-space models

I try to estimate a time-series with an SSM that I built. The problem is that model fit is not very good and I think normalizing variables might help. Both my dependent of some of my independent ...
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2answers
152 views

Why is this time-series stationary?

I am using python for time-series analysis of count data and came across a problem where I have a time-series that to me looks non-stationary but the Augmented Dickey-Fuller test (implemented in ...
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23 views

How to estimate Vector Error Correction Model in a linear equation

I am confused about the Vector Error Correction Model (VECM). The main objective of my study was to determine the effects of public expenditure components on economic growth over 35 years. GDP is the ...
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2answers
33 views

segmentation of univariate irregular time series

this is my first post. I have an irregular time series that exhibits large shifts in both mean and in the direction of the trend. It looks something like this (though this is far cleaner than ...
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1answer
9 views

Coefficients for regression in levels from estimated first difference coefficients

I would like to know if there a simple way to compute coefficients for a regression in levels after having estimated a regression in first differences. Having estimated $$ y_t - y_{t-1} = a + ...
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1answer
22 views

Two-step Engle and Granger's procedure

If I want to check if there is cointegration between $X_t$ and $Y_t$ in the following model, is it enough to check p-value of Breusch-Godfrey test? The maintained hypothesis in this test is no ...
3
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1answer
65 views

How to interpret and do forecasting using tsoutliers package and auto.arima

I have got monthly data from 1993 to 2015 and would like to do forecasting on these data. I used tsoutliers package to detect the outliers, but I do not know how do I continue to forecast with my set ...
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0answers
22 views

Specifying integration level of time series

How to specify the level of integration of $X_t$ in such case? I am familiar with testing integration in R, cointegration strategies, but which method to use in such case? In brackets there are ...
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9 views

Autocovariance Estimation and Stationary Processes

I am going to work on a project involving time series and therefore I am trying to understand some basic definitions. I am currently trying to grasp the autocovariance estimation procedure. When we ...
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1answer
45 views

How can correlation be 0 in % terms but 0.5 when measured in dollars?

I am trying to see if there is a causal relationship between Marketing Spend and Revenue on a monthly basis for the Jan to July 2015 period. I calculated the percentage change in Spend and the % ...
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3answers
26 views

Need time series visualization software with zoom [closed]

I am responsible for providing time series data to my co-workers monthly as line charts. The plots consist of two series: the actual data and a moving-average smoothed line. I am currently doing this ...