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

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How to interpret these acf and pacf plots

Following are acf and pacf plots of a monthly data series. The second plot is acf with ci.type='ma': The persistence of high values in acf plot probably represent a long term positive trend. The ...
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1answer
76 views

Methods of fitting a dynamic linear model

I'm taking a time series course and am learning about exchangeable time series form of dynamic linear models (DLMs). This is given by: \begin{align*} \mathbf{y}_t' &= ...
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1answer
47 views

Difference between different autoregressive models

I am trying to understand the difference between these three different specifications of an autoregressive model for variable var in Stata: ...
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7 views

Frequency analysis from time dependent data in R

I've got a time dependent data from animal recording. My data has two groups (TR and UT) each group has 20 replicate. Tiempo (time) variable goes from 282 sec to 318 sec. I have a turning point at 300 ...
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1answer
134 views

ARIMAX model's exogenous components?

Does anyone know, considering an ARIMAX model that fitting a stationary process Y, then do the exogenous components for the model need to be (weakly) stationary? I think exogenous components can be ...
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14 views

Identify distribution change [on hold]

I have a categorical variable Product that can have one of $4$ possible values, ${x_1,x_2,x_3,x_4}$ The current distribution is ...
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2answers
37 views

Correlation Coefficient for lag $k$ in Time Series Data

Formula of Pearson Correlation Coefficient is : $$r_{xy}=\frac{\sum_{i=1}^{n}(x_i-\bar x)(y_i-\bar y)}{\sqrt{\sum_{i=1}^{n}(x_i-\bar x)^2}\sqrt{\sum_{i=1}^{n}(y_i-\bar y)^2}}$$ In Time series ...
2
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1answer
148 views

Nearly constant time series

I want to analyse temporal interactions of some time series by means of the Box-Jenkins approach to find out which time series are predictors of another one (with the help of prewhitening and ...
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1answer
17 views

How can I estimate the delay between two non-periodic time series?

I'm wondering what the best way to estimate the delay and confidence between two non-periodic time series would be. Specifically, I thought it would be interesting to look at the different economic ...
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13 views

Strong drift in residuals with weighted linear regression

I am regressing two related time series and modeling the residuals as an Ornstein-Uhlenbeck process. I wrote a parameterized weighting function to assign higher weights to more recent values, then ...
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2answers
104 views

Has anybody ever found data where ARCH and GARCH models work?

I'm an analyst in financial and insurance fields and whenever I try to fit volatility models I obtain awful results: residuals are often non-stationary (in the unit root sense) and heteroskedastic (so ...
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17 views

Forecasting one dataset using data and correlation from another using R: commercial centers entrances and restaurant sales figures

Please, be kind, as I'm totally noob in stats and R... I'm the owner of a small restaurant in a commercial center, and I managedd to collect two main dataset, commercial-center (cc) and restaurant ...
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1answer
964 views

Simulate ARIMA by hand

I was working on ARIMA in R and I am trying not to use library forecast as much as possible. I have a code for finding the best ARIMA model, but it is showing some ...
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1answer
25 views

Autocorrelation or Serial Correlation

Autocorrelation is also known as serial correlation . Why is the terminology serial used ? Is there anything unserial or ...
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2answers
112 views

On forecasting, the mean squared error and realized volatility

Say one has finished estimating a correctly specified GARCH(1,1) on a daily time series and now wants to evaluate the accuracy of the one step ahead forecasts what steps or tests could one do? I ...
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1answer
33 views

Testing two raters' time-point data for interrater reliability

My data consists of two raters interpreting one specific phenomenon to occur at different points in time (the observations are not paired, the raters actually identified different amounts of ...
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1answer
117 views

Timeseries Analysis

I have the weekly time series data from 2011 to 2014 with 6 variables (Gross_Revenue, Attendence, Enrollmentcount etc.) and its having seasonality. I want forecast the Gross_Revnue for 2015 1st 15 ...
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1answer
25 views

Predict time series data from another

Here is my problem: I have two times series which are highly correlated. One of my time series have one more data point. I would like to predict the other time series missing data. For example (in ...
2
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1answer
83 views

markov chain with probability trends

I have clients with debts that can pass from states own 1 bill, own 2 bills, own 3 bills, leave the service, new debtors and owe nothing. So I could calculate the probabilities of being in state ...
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18 views

Statistical evaluation of two time series

I have two time series. I want to know, how strong they differ from each other. Very important point is to show that for example all (or probably only the majority of the) points in the first serie ...
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1answer
32 views

Is Predicted R-squared a Valid Method for Rejecting Additional Explanatory Variables in a Model?

I'm building a model to understand the important drivers from a set of possible drivers for a time series of data. In my case the possible drivers are other time series. Like most statistical models ...
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39 views

Fitting a time series model to potentially seasonal data

I'm analyzing a data set that appears to be seasonal but I can't figure out the appropriate model. I made ACF/PACF plots of weekly data of data over 5 years, but I just don't know where to go from ...
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19 views

Time - series analysis data set should be converted to return or taken its Ln?

I'm studying time series in E-views. And I want to investigate Granger - causality between exports imports and economic growth. So, I'm doing causality and co-integration analysis. I have export, ...
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1answer
21 views

Ljung-Box statistic / AR-GARCH weak predictions

How would you interpret the Ljung-Box statistics in the following AR-GARCH output? What is the difference between the $R^2$ and $R$ Ljung-Box statistics? Does the GARCH model seem to be effective, ...
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3 views

What measures can be applied to the arrival of unique website visitors to asses whether there is an increasing or decreasing trend?

I am looking at the logs of arrivals of unique visitors to a website. I can plot the data as a histogram, and look at the plot to get an idea of whether there is an increasing or decreasing trend in ...
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31 views

ARX model selection

I have an autoregressive model with exogenous variables: $S_{t} = \sum_{i=1}^{p} a_i S_{t-i} + \sum_q \sum_{i=1}^{r} b^q_i X^{q}_{t-i}$ where $S_t$ is the signal I want to predict and $X^q_t$ the ...
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1answer
660 views

Transfer functions in R (TSA package)

In Time Series models’ transfer functions there is a decay parameter in the formula (let’s call it b). In TSA package that decay parameter is not mentioned. When I used other software before (such as ...
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32 views

Adjusting for the past using OLS regression with single lagged response

There are many fine ways to handle a time series error structure in regression, for example as discussed in Time Series with Autoregressive Error. But consider a panel regression model of the form $$ ...
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1answer
62 views

Using the Weibull curve to model responses from a direct mail campaign. Model isn't fitting the data very well

I'm trying to build a model to forecast direct mail marketing campaign responses. In the "response" vector are the average number of responses from a marketing campaign from day 1 to day 63 (8 weeks). ...
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15 views

Aggregating Multiple Sparse Time Series

My data contains multiple time series, each representing a person's activity over time, grouped by month. The activity is defined by a single count variable indicating the magnitude of their activity. ...
2
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1answer
395 views

How to apply an AR(MA) model to a prewhitened signal?

I have two (vehicle velocity) signals that should consist of similar "latent" drivers, but have different autocorrelation structures. The driver-signals are quite nasty statistically, so I'm not ...
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2answers
39 views

How to test predictive power of GARCH model

I ran the following code in R using the fGarch package to get estimated coefficients for a (1,1) model: garchFit(formula = ~ garch(1,1), data=hubtimeseries) It ...
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2answers
52 views

Which econometric models can be used to forecast security returns + ARIMA/GARCH questions

I'm trying to write an undergraduate thesis wherein I test the predictive power of a given econometric model on a given financial time series. I need some advice on how I should go about doing this. ...
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20 views

Weekly frequency [on hold]

I'm analysing weekly time series data. Years have different numbers of weeks, some 52 and some 53, but by time series assumption it has to be constant frequency. How can I fix frequency problem?
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9 views

How to know regression equations at optimal combination method for hierarchical time series forecasts? [on hold]

I'm doing a comparison about forecasting hierarchical time series methods and I would like to know better how does optimal combination works (method proposed by Atanasopoulos, Hyndman and Ahmed). I ...
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1answer
18 views

Multiple Independent Variables, Multiple Dependent Variables and Time Series Data

I am conducting a research on stock market. My Independent variables are Oil prices, Exchange rate, Interest rate, GDP & Inflation. And Dependent variables are Market return, and Sector wise ...
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1answer
216 views

ARIMA, adjustments and intervention analysis

I have very little knowledge of time-series analysis (despite my stat master - didn't do anything else than an introductory course) but now I'm facing a statistical problem whose answer is this very ...
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28 views

Sample time series to equal interval

I have data with timestamp and associated values. time interval between two consecutive data is not constant. How to standardize the the time series and associated value ? eg- Input data is Timestamp ...
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1answer
69 views

Regression with autocorrelated, lagged independent variable

Dear Cross Validated Community I have a question about handling dependencies in time-series regression. This is not an urgent issue. However, it would be nice to have a little discussion here - if ...
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18 views

Considerations for forecasting

I am trying to make a generic forecaster for many short (~14 points) to long term (~365 points) time series data assuming the seasonal period to be weekly. The predictions are going to be made for a ...
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1answer
192 views

Generating IMA(1,1) series

I'd like to generate a series that follows an IMA(1,1) process, where $θ$ is the moving average parameter. I generated the series based on different representations and I got different results, I'm ...
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1answer
1k views

Difference between series with drift and series with trend

A series with drift can be modeled as $y_t = c + \phi y_{t-1} + \epsilon_t$ where $c$ is the drift(constant), and $\phi=1$ A series with trend can be modeled as $y_t = c + \delta t + \phi y_{t-1} + ...
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474 views

Correlating time series for 20 regions (SPSS)

I have a question to which I can't find an answer although I spent really awfully lot of time searching. I have time series data for about 20 regions of a country. Each time series covers 20 years. ...
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2answers
29 views

Intuition for auto-correlation for mean reverting process

How should my auto-correlation plot look like for a mean reverting process? From what I have recently learned, auto-correlation should be low and should decay fast enough. But when I run the following ...
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1answer
24 views

Stationary dependent variable

When running a time series, the Dickey-Fuller test of the dependent variable is statistically significant, meaning that it is stationary (which is also confirmed by looking at a plot of the variable). ...
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12 views

Multiple Independent Variables, Multiple Un-correlated Dependent Variables and Time Series Data

Which Model is best for Multiple Independent Variables, Multiple Un-correlated Dependent Variables and Time Series Data. Which Model or Technique will be suitable to run the test just one time analyze ...
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0answers
20 views

Best way to select parameters to SARIMAX model

I am trying to understand what is the best way to find the hyper-parameters for an SARIMAX timeseries model, this has 4 additional parameters (P-AR parameters,D-differences,Q-MA ...
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1answer
124 views

Cointegrated Vector ARMA (CVARMA) Model vs. Dynamic Factor Model (DFM)

Two questions regarding the equivalence (or lack thereof) of vector error correction model (VECM) cointegrated vector ARMA model (CVARMA) and dynamic factor model (DFM): Can every VECM CVARMA be ...
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3answers
56 views

Trend Analysis: How to tell random fluctuations from actual changes in trends?

I hope somebody in here can help me: I'm looking for some pointers as to how to distinguish random fluctuation from actual changes in trends, e.g.: In a time series with measures taken at monthly ...
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40 views

Interpreting Granger Causality F-test

This question is a bit basic (I reviewed the previous postings on similar subjects, but still need help with this). Thanks in advance for any answer. The question is if A & B are two time-series ...