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

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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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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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23 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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17 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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24 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 ...
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22 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 ...
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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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1answer
31 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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18 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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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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30 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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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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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. ...
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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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19 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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32 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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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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17 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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31 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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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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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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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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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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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
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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Modeling Non-Stationary Time Series Data

Data set: response and predictors are all non-stationary, time series variables After performing Box-Cox transformations and testing a variety of power transformations on each variable, the ...
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Does the order of variables in a Markov Regime Switching model matter?

since Ive received feedback that my previous question was not well-recieved Ill just have to give it another shot. I am estimating Markov Regime Switching Models, and I am getting different results ...
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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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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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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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20 views

MCMC estimation for multivariate stochastic volatility model [on hold]

how can i estimate multivariate stochastic volatility models with R or WINBUGS for daily exchange rate data
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37 views

How can I determine if a time-series is statistically stable?

I have time-series data that tracks the number of sydromics records my organization receives each week. The number of records had been steadily increasing as more organizations started sending us data ...
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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 ...
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Why and when stationarity is achieved by decomposition rather than differencing in ARIMA model

I would like to understand relationships between variables by which cross-correlation function, that means what is the extent one variable influence the other one. ARMA model is used to fit two ...
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84 views

ETS() function, how to avoid forecast not in line with historical data?

I am working on an alogorithm in R to automatize a monthly forecast calculation. I am using, among others, the ets() function from the forecast package to calculate forecast. It is working very well. ...
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Is it advisable to average quarterly benefit claimants rate to an annual claimants rate, and if so how?

I had a discussion with colleague whether would it be sensible to average quarterly unemployment benefit rate to an annual rate? Is it better to refrain from averaging the quarterly ...
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Is $MA(\infty)$ process invertible?

Let us say $X_t = \sum_{i=0}^{\infty}\phi_j Z_{t-i}$, where $Z$ is white noise. Is $MA(\infty)$ process invertible? I don't know how to show this, because $\theta(z) = 1 + \phi_1 z + \phi_2 z^2 ...
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28 views

Coefficient for a zero lag cross-correlation different from Pearson correlation r

Reading around I understood that using a cross correlation with lag zero should give the same results of a normal pearson correlation. It happens that this is not the case for me. What could be the ...
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31 views

Associating non-linear three-time-point change with a continuous variable

I would be incredibly grateful for help or advice regarding my following project: I have 3 time points (0, 30, 120 min) and complete data for about $n=500$ subjects for a continuous variable $M$. ...
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38 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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22 views

Descriptive and Inferential Statistics

I am doing a time series analysis (stock market returns) and I am currently looking at the summary stats. I know the definitions of the individual stats but the one I am stuck on is the relationship ...
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What can I know about time indepence from ACF and PACF plots?

Question: In which series do you find stronger time dependence? I was reading slides provided by the professor and I didn't even find the word "time dependence". By saying a series is "time ...
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1answer
31 views

Comparing two sets of data over time to infer correlation or imply causation

I have two data sets, over a period of time that I would like to compare. I am very unfamiliar with statistics so sorry if this is simple. I need to use SPSS. I am comparing the number of journal ...
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34 views

How to simulate a third order AR model

I'm trying to understand AR models but it's getting pretty difficult for me. Just wanted to ask you some hints on how to simulate an AR(3) model driven by a zero mean WN for 1000 values in Matlab, ...
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20 views

How to build separate time series forecasts model for each of 3k customers?

I have 3000 customers in my base and i want to forecast next 6 months revenue for each of these 3000 customers. Does that mean i have to build 3000 arima models 1 for each customer? I can build a ...
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36 views

Fitting an ARCH/GARCH Model (Basics)

I have been given a basic task designed to assess my knowledge of ARCH/GARCH modelling, which involves fitting the models on 2 lots of time-series index returns. What are the brief steps I need to ...
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Handling non existent observations [on hold]

I have several variables (time series) ...
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39 views

Using a rolling window in time series regression

I am learning about regression. I have done some cross sectional regressions which are fine. I recently did a simple time series regression. So I have a y & x vectors each containing 1000 ...