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

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Survival analysis with time dependent covariates and cured fraction

I have a problem specified in this way, I'll make a fictional example, because the actual data requires quite a bit of domain knowledge to be understood. There is a series of newborn babies (let's ...
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25 views

Why do you have to use MLE instead of OLS in time series data?

I know it has something to do with the errors being correlated with the variable, but I'm not sure exactly what that means. Could someone please give me a quick simple explanation about why you must ...
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25 views

Interpreting regression results

I computed the following regression using R. ...
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8 views

How to test the significance of the Hurst parameter?

I am trying to fit a FARIMA model and I am using rsFit function in R to estimate the Hurst parameter (H). This function provides ...
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17 views

Vector autoregressive model selection process and relationship with cointegration

Let's say you're looking at two securities that trade closely with one another and you suspect you can somehow trade the spread. How can you use VAR models to estimate the relationship between the ...
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1answer
122 views

R Time Series Analysis forecast result always remains same

I am trying to do time series analysis in R. I have data time series data set like this. ...
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1answer
9 views

Using Diebold-Mariano test to compare predictive errors in non-time-series?

I understand that the DM test is established for time series data, but could I still apply the test for non-time-series data? Could I simply replace the autocorvaiance part of the test statistics with ...
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20 views

Appropriate Test for Statistical Significant Change in Values Over Time [duplicate]

I have four number of values for number of policies within a given field put forward in a given year. I want to find if there is a statistically significant increase or decline in the number of ...
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14 views

How to determine significant difference between two sets of time series data?

I have 2 sets of time series data. The data were collected from individuals who were matched (via propensity score matching) prior to collection. The only difference is that one set of matched ...
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12 views

orthogonalized impulse response's contradictory forms in a VAR(p) model

I have so far discovered three different ways of utilizing the Cholesky decomposition for calculating the OIRFs of a VAR(k). The different methods seem contradictory so I would like some input on ...
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15 views

How to find if there is a trend in a time series and stationarity

I would like to conclude on a given time series that if it has Trend or not. I have carried out a cox-stuart test in R and have decomposed to inspect the series visually but still a bit confused on if ...
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23 views
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32 views

Forecasting and decomposition of hourly time series with 2 seasonal periods

I have hourly temperature data over a 5 year period with a lot of missing values. They have 2 seasonal periods: daily (24) and annual (365*24). I am very interested in the diurnal cycles of the ...
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1answer
42 views

Correlation between spot and futures

I am Airliner.I want to protect my business from price volatility of jet fuel cost.Jet fuel is not traded in futures market but Crude oil is traded in futures market. I have daily spot prices of jet ...
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1answer
40 views

Introductory data trend analysis with R [on hold]

I am new to the data analysis world and am struggling to find relevant articles / examples related to what I'm trying to do. I have a data set that is like this, for example how many apples are sold ...
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10 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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2answers
98 views

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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18 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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1answer
21 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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20 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
29 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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19 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
27 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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2answers
40 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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14 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
33 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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23 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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4 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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33 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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113 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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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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21 views

Weekly frequency [closed]

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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10 views

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

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
20 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
36 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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31 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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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
60 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
44 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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34 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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2answers
32 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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13 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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21 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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21 views

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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1answer
22 views

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
60 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 ...
2
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2answers
53 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
67 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). ...