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

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53 views

Interpretation of DCC-GARCH output

I have done fitted a DCC-GARCH model using the dccfit function from the "rmgarch" package in R. The output is below: ...
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14 views

How to analyze Time-Series Panel Data with Binaries?

For a project I have collected some data. The Data has some binary variables (success(0/1), Manager present(0/1), First_Third (1 if the observation was in the first third of the project, 0 otherwise) ...
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60 views

Cross-correlation between two seasonal series

To determine cross-correlation between Sales and Variable cost, both having monthly seasonality, do I need to de-seasonalize ...
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3 views

How to use weight and correlation options of the nlme–package to define complex covariance structures?

At the moment I try to explore the various options of the gls-function which is implemented in the nlme-package. The data that will be analysed with it are repeated measures with random intercepts, ...
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20 views

How to quantify the relationship between Social Media Sentiment and Monthly Sales time series data

I'm doing a side project at school which is to understand if there are any causal relationship between social sentiment data and sales (either good/neutral/bad comments from facebook or tweeters will ...
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21 views

Gaps of methods to evaluate prediction accuracy

There are many methods to evaluate prediction models based in prediction errors, such as MSE, MAE, MAPE, WMAE, etc. These methods are usually used in data prediction competitions, where one is given a ...
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27 views

Accuracy of time series predicton

I have two time series - actual and predicted. They both can be positive or negative, can jump or remain constant, one can be positive other can be negative - basically any combination is possible ...
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1answer
31 views

Reverse forecasting in time series

we have a given time series includes a specific type of data for example from year 1980 to 2016. Also we know that we should achieve to a predefined goal(a fixed value) in year 2025. But we don't ...
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15 views

which test to measure the trend in sales in R

I have sales data of an online store that is based in 4 countries. The Co. sends out Newsletters through out the year and found out at the end of the year that it sales from the newsletters has ...
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13 views

Searching for an inverse in a time series [duplicate]

Suppose $(1-B)y_t=(1-B)a_t$. Does this imply that $y_t=a_t$? $B$ is the backwards shift operator defined by $Bz_t=z_{t-1}$. $a_t$ is a random shock with mean 0 and variance $\sigma^2$. ...
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82 views

Does this Monte Carlo Technique Have a Name?

I sketched this algorithm out the other night. I am sure it has a name, I just do not know what it is yet. It would be helpful if someone could point me in the right direction for research. I ...
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80 views

How to assess seasonality effect influence on time series

Suppose I collected a time-series data (e.g. drug prescription on every month for 12 years). I have no reason to believe that my data is influenced by a seasonal factor (e.g. drug consumption is not ...
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11 views

Correct output labelling for RNNs/ANNs with sequential data and single label

I have a labelled time-series dataset; for example, a sequential input length $n$ from $k$ sensors corresponds to class '1' (see below for $n=50, k=2$). How can I correctly classify it? If I use RNN ...
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35 views

Multiple exogenous IV 2sls in Stata

In my model I have two exogenous variables which I want to use as instruments. Can you please help me with Stata code for it? I assume it should be something like this: ...
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1answer
35 views

Bayesian time series - more weight on recent observations?

Note: I'm a stats novice, please let me know if any of these terms are unclear or misused and I'll update the question! I'd like to predict future values of a time series. More precisely, I'm ...
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2answers
82 views

Is this a nonlinear time series?

Could someone please help me to find out whether a time series is linear? And if it's nonlinear, what degree of nonlinearity? I searched for an appropriate function in Matlab, but it seems there's ...
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59 views

I have the equation (1 − B)yt = (1 − B)at, can I conclude from this that yt=at for all t?

I have the equation $(1 − B)y_t = (1 − B)a_t$, am I able to say that this equation implies that $y_t = a_t$ for all t? $B$ is the backward shift operator where $Bz_t = z_{t-1}$ and $y_t = y_{t-1} + ...
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19 views

how to compare ARIMA and exponential smooting model numerically

The exponential smoothing method gives us values like SSE and $R^2$ for the entire model. The ARIMA model, however, does not give us these values. So, given the same data, how do one decide which ...
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18 views

Recommended Reading - Covariance & Correlation in R for Time Series [duplicate]

I'm at the beginnings of trying to find this out, and much of the reading out there is not quite what I'm looking for. I'm looking for recommended reading for determining correlation or covariance ...
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27 views

Normalise heart rate data

I need to statistically examine time series of heart rate data over many different users. Since I don't have data for each user for each instance, I should find a way to normalise the data so that I ...
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1answer
102 views

Relationship between cointegrating relationship found via PCA and that found via a Johansen test

Thanks to the explanation given here: PCA on prices or returns I understand how PCA can be used to derive cointegrating relationships. However there is of course another well known method to ...
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12 views

rolling window for time series- permutation issue

Suppose that I am interested in a one step-ahead prediction of the value of some time series, and I want to use, let's say, a Support Vector Machine to do the task. A very common way to set up the ...
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34 views

Estimation of autoregressive parameters of an AR(1) [duplicate]

I'm studying inflation and in particular its persistence, that is measured by the sum of the autoregressive parameters. Inflation time series is usually modeled in literature as an AR(1) process $$y_t ...
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19 views

Where can I found an implementation of a dynamic panel data model with garch in mean effects in R, Python or other language?

Where can I find an implementation of models such as the ones described in Cermeño and Grier (2001)? This is particularly interesting to estimate risk-return relationships using cross country data.
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91 views

PCA on prices or returns

This question has been addressed here: Can Principal Component Analysis be used on stock prices / non-stationary data? In his answer Jon Egil wrote please make sure you analyse returns not ...
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31 views

help with econometric model

I need a help with my econometric model. I have never studied the subject and now I need to use it in my work. I am assessing the impact of the Indian commodity exchange on the producers. more ...
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11 views

State Space Model Specification (KFAS)

I am using KFAS to fit a dynamic logistic model of the form; $\hat{y} = \bf \beta_t x + \epsilon$ $\beta_t = \beta_{t-1} + \eta$ So the regression parameters change over time, and act as latent ...
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22 views

How to interpret AR(1) parameter estimates from SAS time series forecasting system?

I am attempting to fit an AR(1) model to some synthetic data, to become more familiar with the time series forecasting system in SAS. In my understanding, such a model would be of the form X(t) = c + ...
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20 views

Why filtering for trend estimation?

I'm starting to learn about techniques for trend removal of a time series with no seasonal component, i.e. $X_t = m_t + Y_t$. If I undertsnad correctly, there are all sorts of filter we can apply in ...
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32 views

Find a window of ‘best correlation’ – exploratory analysis

I have data from a neurobiological experiment and I'm interested in learning which parts of multiple time-series (e.g. event-related potentials) best explain behavioural data (e.g. accuracy). Rather ...
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21 views

Multiple Seasons msts R fpp

I am trying to use the fpp package to do some forecasting in R My figures are daily and the seasonal trends include week, month and year. Week and year seem easy: y <- msts(x, ...
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21 views

What techniques I should look to predict next user behavior in a series?

I have a dataset, when users repeat an action (let's say, to choose a value between 1 and 10) many times (let's say 10 times). I want to predict the behavior of users at the 10th action, based on his ...
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92 views

Periodicity and seasonality of a time series

I have a time series and I have done some spectral analysis on it. When doing an autocorrelation and periodogram it shows that the time series is periodic. However when I do a Dickey-Fuller test it ...
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135 views

Granger causality and non-linear regression

I’m new to Granger Causality concept. I know that the “Granger causality” is a statistical concept of causality that is based on prediction. According to Granger causality, if a time series X ...
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39 views

How to calculate interim and long-run multipliers in ARDL models with >1 lag?

I have calculated an ARDL(24,36) model with 1 independent variable. The data is monthly, hence the inclusion of so many lags. I am trying to calculate the interim multiplier (the cumulative effect at ...
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25 views

How to use RMSE when having data normalization?

I am new in machine learning and I am studying time series prediction using neural networks. Pseudocode 1: ...
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28 views

Time series as stationary stochastic process

(This is a homework problem.) Check if the following series is covariance stationary: $$ \newcommand{\if}{\text{if }} Z_t = \begin{cases} X_t &\if t\text{ is even}, \\ ...
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1answer
42 views

Monte Carlo rolling forecast of time series - details needed

I know I'm doing a short term forecast of a volatile time series using Monte Carlo, but I'm unsure as to the details - for example, I'm sure I had a very good reason for naming a term 'drift', but I ...
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22 views

Time-series with RNN - how to deal with attributes that span entire sequences?

I am currently trying to train recurrent neural networks for time-series forecasting, and I'm having trouble figuring out how to properly deal with attributes that stay constant over each series. For ...
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75 views

Correcting autocorrelation with MA in a regression

I would need some advice on a multivariate regression problem. I am running regressions with macroeconomic data at first difference and using a AR(1) as regressor to correct autocorrelation (it makes ...
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51 views

What is this time series model and how to produce it in R?

I know that $Y_{t} = a + bY_{t-1} + \epsilon$ is named as autoregression model. I am dealing with the model like: $Y_{t} = a + bY_{t-1} + cX_{t} + dX_{t-1} + \epsilon$. I could not find any useful ...
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1answer
59 views

Testing significance of cross-correlated series

I want to prove that, overall, signal B is correlated to signal A. I was thinking of using cross-correlation (in R) to measure this. Essentially I have two kinds of signals: signal A is a series of ...
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37 views

(S)ARIMA — Hints with Time Series

I am a beginner in time series analysis and I would like discuss a couple of numerical examples here implemented in R. I am reading some interesting books, but I also need some expert advice to get ...
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13 views

How to find correlation of a response variable with multiple predictors for a time series data?

How do you find the correlation between a response variable and multiple predictors with time series data? I need to study the trend of a variable vs other variables for an entity.
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24 views

How can I test for seasonality when the trend is not supposed to be monotonic but sinusoidal?

My knowledge of time-series analysis is limited. So far I have only assessed whether there was a seasonality in my time series data with the assumption of monotonic trend. To test that I would have ...
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5 views

Is it possible to combine linear VAR restrictions with SVAR A/B restrictions?

I have been exploring the various restrictions that are commonly applied to (S)VAR models in textbooks on multivariate time series, noting that linear restrictions on VAR models seem to be treated ...
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41 views

How to forecast weekly sales data using R and `auto.arima`?

I have weekly sales data with for thousands of products which I want to forecast in an automated manner. What I clearly observe in my data is that there is a weekly skew within a month (wk1 sales < ...
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39 views

Time Series: Normality

I have a time serie, and I want a stationary process for search posible models. One of the requirments is normality. shapiro.test(serie) p-value = 0.0002322 How ...
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14 views

Is the following a standard HMM variant?

I have a problem that looks to me like a HMM variant. Could somebody confirm that I am on the right track modelling this and possibly tell me the name of this HMM variant if it is a standard HMM ...
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32 views

Financial time series data: Imputing before or after calculating returns?

I've got several time series of daily prices ($(p_t^j)_{t=1,\dots,n}$ ) of different tradable cards $j=1,\dots,k$. I'd like to calculate the time series of the (log)returns $r_t= ...