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

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Best way to forecast hourly data

I have a time series of hourly data for 3 years. I want to find hourly forecasts using this set of historic data. My data has hourly, daily and annual seasonality. I first read my data into a ...
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1answer
67 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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5 views

Time points density

I have a date-time points and I want to visualize the density of them in time. How can I calculate the density of this time points for example in a 1 minute or 1 hour intervals or what ever. Thanks
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21 views

Interpretation of autocorrelation plots using ccf in R

I'm not that familiar with time-series type data. I am looking for some advice on the interpretation of the following plots of autocorrelation between two variables. I used ...
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27 views

Time Series Stationarity and Histograms

In a paper I am reading, the author discusses stationarity and plots the histogram of returns for the time series he is studying. I was wondering if there was any relationship between stationarity of ...
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42 views

Interpreting Correlogram

I am wondering if anyone has any ideas as to how to interpret the following correlogram? Or in general, what is the best way to treat/interpret a correlogram that exhibits a curve
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1answer
57 views

Time-series and autocorrelation inequality

I am having problems proving for a weakly stationary process $\{X_t : t\in T\}$: $\rho_X(2)\geq 2 (\rho_X(1))^2-1$ where $\rho_X(j)=corr(X_t, X_{t+j})$. So far I have shown that $-1\leq ...
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44 views

Accuracy function in R [migrated]

I Want to compute the accuracy of a numerical vector that contains 12 forecasts but I get this result with a warning. ...
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8 views

How do I use CCF for multiple time series variables in a matrix? [migrated]

I am trying to compute the cross-correlations for my dependent variable against a matrix of independent variables (all monthly data) in R. In other words I have one dependent variable (Y) and want to ...
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1answer
44 views

Linear regression vs Time series analysis

I am confused that when I should use static model (like cross-sectional regression) or other forms of time series model. I see some examples of analyzing time ordered data by crosss-sectional ...
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34 views

analysis of bank account record

I am new to the field of time series analysis, but I would like to have a look at my bank account and determine my spending habits. I read a lot about clustering of multiple time series but I think I ...
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29 views

Classification of time series with SVM

Background: I'm currently trying to find interesting anomalous interferences in time series data. I have quite large database of collected data with many different measurements (over 2k measurements ...
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1answer
14 views

Which method is suitable when the independent variables are of process steps over time and the dependent is binary?

I'm quite confused with some methods I've read about - growth models, repeated measures, time-series fixed effects models etc. I'm trying to understand which method is most suitable to the data I ...
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54 views

ARMA models and invertibility

I'm reading the book Time Series Models by Franses et al. It says that if we have an $ARMA(1,1)$ model with $\phi=1$ and $\theta=-1$ we have $y_t=\epsilon_t$. So, this means that in the equation ...
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2answers
72 views

Does possible non-stationarity matter if the model is OLS?

I am working on an assignment where the current model is an OLS model that models the percent change in a variable, X, by regressing it against a bunch of economic variables such as unemployment rate, ...
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13 views

Method needed: parameters leading up to an event

I apologize, this is probably a simple question. I have 3 or 4 time series variables (temperature, depth, etc.) and I have the times that a specific event occurred (about 100 different events of the ...
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1answer
61 views

How do you generate correlated ARMA(1,1) models?

I am interested in generating two ARMA(1,1) time series with a pre-defined cross-correlation p between x(t) and y(t). If you could please provide the mathematical framework and the code in R for ...
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16 views

How to predict values? [duplicate]

I have a simple time series with at least a measurement a day. I would like to know if there are algorithms that can deal with missing values and measurements that are not taken always at the same ...
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19 views

Question about ADF-test on currencies, and how to test for non-linearity (Regime switching models)

I am writing a document about currencies and regime switching, and Im thinking about testing for stationarity and then non-linearity. There are some litterature about how poor the ADF-test works on ...
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13 views

Discrepancy between hierarchical top level time series and direct sums - using package hts

I have an xls file with sales data from 12 shops, each selling two types of goods. If I read in the xls file and sum up sales for each month (ignoring the two types of goods and just looking at the ...
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44 views

Any machine Learning models to predict dates?

I have a general question regarding machine learning models. The idea is to predict what DATE the customer is likely to make transactions or purchases. Variables present in the data set are item, ...
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14 views

Why do orthogonal complements come into play in the Granger representation?

Consider the Granger representation of a VAR model. (See : here). Can anyone explain me how in this representation Equation 1, page 4 the orthogonal complements of $\alpha$ and $\beta$ come into ...
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1answer
27 views

Is autocorrelation also a problem with data collected from different respondents?

I have a question regarding autocorrelation in multiple linear regression. I analyse data on IPOs over 6 years. I look at a dataset of 450 companies which have listed their stock at the stock ...
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1answer
52 views

How do you simulate two correlated AR(p) time series?

I would be interested in the mathematical framework plus code in R if possible. Basically I want to find out the parameters of the two AR(p) models if I already specificed a certain cross-correlation ...
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1answer
27 views

How to apply cross-validation for time series analysis using a regression-based approach?

I'd like to know how to use cross-validation for time series analysis using a regression-based approach without incurring in under- or over-fitting. In particular, assume we have an input time series ...
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12 views

Time Series Analysis - Object in R [duplicate]

For a time series object (in terms of theory/concepts), do we have to have the data for each date? In some cases the customers do not make purchases/sales amounts during the same month. For example, I ...
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2answers
56 views

How do you count the number of parameters in a time series model?

I am learning about time series analysis and want to perform Box-Ljung tests of the residuals of my fitted models, e.g. ...
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1answer
31 views

Sequential pattern matching in time series data

If I have a time series set such as x=[0,2,5,2,3,1,0] that represents an artifact. What is the best way to match a similar set as x in a larger data set y?
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11 views

Bayesian Graphical Network with Time Series

I am not so strong with Time Series so I thought I'd ask here. I am working on a Bayesian Graphical Model where I have observations recorded once a day. So obviously, there is some influence of time ...
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1answer
44 views

Comparison of Two Time Series (Strategies) - Are they different?

Apologies for my naivety if the answer to the question is simple, stats is an area I am not comfortable in and am looking to improve. My problem is within the frame of finance. Simply put, say I ...
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21 views

How long does it take two identical hidden Markov models run on same observations to forget their initial distributions (if ever)?

Let $H_1$ and $H_2$ be two instances of a finite Hidden Markov Model (HMM) $H$. That is, $H_1$ and $H_2$ have identical state spaces $Q$ as well as identical transition $A$ and emission probabilities ...
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16 views

Averaging time series to improve stationarity - loss of power?

Short version When averaging over a presumed stationary time series and calculating statistics (e. g. normalized mean square error) to compare to a simulation (atmospheric turbulence model) of the ...
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26 views

Autocorrelation function in R for observational data

I'm trying to replicate an analysis done in Stata with R that involves calculating the autocorrelation for a particular outcome measured in many different areas. I've already run a linear regression ...
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1answer
54 views

modeling time series data with lm()

After you decompose a univariate time series with stl() function in R you are left with the trend, seasonal and random components of the time series. Is it valid to use those components to then model ...
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Who first suggested to approximate phases from a time series via marker events?

A rather simple approach to approximating an instantaneous (unwrapped) phase $φ$ from a time series is as follows: Define some a appropriate marker events (e.g., upwards zero crossings) $t_0 < … ...
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1answer
59 views

ARIMA predictions constant

I've created an Arima model based on past forex closing prices using auto arima, which has generated a (0,1,0) ARIMA model. ...
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1answer
91 views

Distinguish an ARMA and an ARIMA model graphically

I'm currently analyzing some time series data and I need to know how to distinguish an ARMA model from an ARIMA model just by looking at the auto-correlation function and partial auto-correlation ...
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9 views

To sketch a “typical” plot of a specific time series model

Let X have a distribution with mean $\mu$ and variance $\sigma^2$, and let $Y_t = X$ for all t. Sketch a “typical” time plot of $Y_t$. My thoughts: This process $Y_t$ is stationary with mean $\mu$, ...
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1answer
61 views

Clarification on ARDL/Unrestricted Error Correction Model

I have a few questions about unrestricted error correction models. The UECM for a model where $Y$ is the dependent variable and $x$ is the sole independent variable is given by, $$ \Delta ...
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23 views

Prediction using categorical, binary and time series variables

I have per subject: categorical variables - ex: grade, mother_education continuous variables - ex: ...
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32 views

Optimizing a time-series with multiple predictors

I have a few questions about turing a univariate time series into a multivariate time series and optimizing the predictors. Here is the univariate data: ...
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1answer
31 views

Panel data: Compare two different assessment methods

Just wondering if anyone has any inventive (but relatively simple) ideas about how to approach comparing panel data from two different assessment methods that collect the same variables. Basically, I ...
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9 views

Sensitivity Analysis of MA Process

Can sensitivity analysis be carried out for a time series moving average process? In a time series process, we wish to shock the x variables and beta coefficients and observe the effect on y. But in ...
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1k views

Why are “time series” called such?

Why are “time series” called such? Series means sum of a sequence. Why is it time Series, not time sequence? Is time the independent variable?
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14 views

Filtering time periods where relationship is swiched on/off

Sorry for the "unmathematical" formulation of the problem to come, but I am not sure where to place my problem: Suppose there exists a relationship between the variables x and y. I can observe both ...
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18 views

Bayesian Time Series Analysis Source

Is anyone able to recommend a source that covers Bayesian time series analysis in Winbugs?
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1answer
26 views

How do panel regression estimates differ from those obtained from multiple time series regressions?

I am trying to familiarise myself with panel regression techniques and I would like to know how the parameter estimates obtained from a panel regression model differ from those obtained from multiple ...
0
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1answer
45 views

Forecasting in Stata

I am working with time series data and fitting an autoregressive model using OLS. For reference, here is my price data for the commodity (I am not sure how to better format data for this site): ...
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26 views

Dependent variable is non-stationary and independent variable is stationary - residual series?

I ran a regression model where dependent variable is non-stationary (I know this is wrong) and my independent variable is stationary...I find that the residual series are stationary... how is it ...
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1answer
23 views

How to make series stationary when dependent variable is log(y)

I need some help in understanding the following: I have a time series data (y) that I am using to run regression models. However, my dependent variable is log(y). Should I test for stationarity of ...