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

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forecasting sharp seasonal peak in time series

I have time series data on a daily level over the past 4 years. What is clear from examining past data is that there are two very clear peaks in the time series around the same time of year (they ...
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17 views

Imputing missing values of predictor for use in Regression Models

I have a panel data set that extends from January 2013 to July 2014. The response variable is complete for the entire period, however all of the predictor variables have values only up to June 2014. ...
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1answer
45 views

Can a Moving Average be used as a dependent variable in a regression model?

I have a time series I want to use as a response in a regression model. The problem is that I suspect that the changes in this variable could be due to sampling error. As a result, I created a moving ...
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8 views

Lumping of data

I have some time series $X = (X_t)_{t\leq T}$ that range over a finite set of values. For each $X_t$ let the next different value $X_{n(t)}$, that is $n(t)\geq t+1$ $X_{n(t)}\neq X_t$ and $X_s = ...
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1answer
54 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 weeks ...
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24 views

Prediction period is coming wrong in the HoltWinters in R

I am Using Holt-Winters model for the forecasting. Below is the way I am proceeding: ...
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15 views

Does forward filtering result in OLS estimate for each time point?

I'm learning about dynamic linear models and was trying to think about the relationship between GLS and forward filtering (Kalman filtering where the state is the vector of parameters). Here's my ...
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1answer
147 views

Beginner learning resources : Pdf and likelihood function for non-Gaussian time series model

I am struggling with exercise problems related to blind system identification where the knowledge about the source input is assumed to be known using maximum likelihood estimation of univariate time ...
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0answers
27 views

Pre processing methods to reduce autocorrelation in Time Series [on hold]

I have an eeg time series data set. Can you suggest some pre processing methods to minimize auto-correlation in time series data? Can PCA and Fourier transformations be taken as methods to reduce auto ...
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1answer
52 views

interrupted time series in R

I have Malaria incidence data from 2003 to 2013. There was intervention implemented in 2008. How can I do segmented regression analysis of interrupted time series in R to test whether the pre ...
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19 views

How to determine Forecastability of time series?

One of the important issues facing forecasters is if the given series can be forecasted or not ? I stumbled on an article entitled "Entropy as an A Priori Indicator of Forecastability" by Peter ...
2
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1answer
18 views

Estimating better performing variation with unkown sample size

Scenario: We are in the app business and trying to optimize for downloads in the app store. Things like the shown screenshots, the text, the icon etc. can be changed and will have an influence on the ...
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2answers
94 views

Is a time series the same as a stochastic process?

A stochastic process is a process that evolves over time, so is it really a fancier way of saying "time series"?
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43 views

How do I solve this stochastic differential equation?

So I have a second order stationary process $Y(t), \infty < t < \infty$ which has a continuous sample function, mean $\mu_Y = 1$ and covariance function $r_Y(t) = e^{-|t|}, -\infty < t < ...
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0answers
6 views

Year to Year-Month-Day format [migrated]

I have a datafile in the following format: ...
0
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0answers
29 views

About comparing two time series

How can I compare two time series? I found this page:How to compare two time series? There is an explanation of ARIMA but I don't really know how the t-test and whole process is carried out. Can ...
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0answers
24 views

time series rolling cross-validation for parameter selection and model comparison

I want to do two things using rolling cross-validation for time series (as in the famous Hyndman's post): select parameters for model A, and compare it's predictive performance with a model B. I'm ...
2
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1answer
39 views

How can I test and quantify the change in distribution over multiple years?

I have a data set of energy usage values taken every half hour for a year, for four years. How can I test for, and quantify, an improvement (i.e. decrease) in energy usage, per-year? I have initially ...
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1answer
42 views

How many observations do I need to implement ARIMA?

I need to model an ARIMA with a time-series data. But my data is the statistics of land area, and it's annual data, so I have 64 points between 1950~2014. Because it increased by a stable rate, So I ...
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19 views

What analysis should I run?

For an RCT, I want to test scores on BES(Binge Eating Scale) and BMI over time for two different groups(experimental and control group)to register whether treatment had an effect on reducing symptoms ...
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41 views

Linear regression with a delay : $R(t)= a S(t-\delta) + \epsilon$

$R(t)$ corresponds to soil respiration values in function of the time $S(t)$ corresponds to solar radiation values in function of the time $R(t) = a S(t-\delta) + \epsilon$ How calculate the ...
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2answers
58 views

How to interpolate a variable with frequency of 5 years to annual data?

I have two time-series variables: each has 14 points with an interval of 5 years. The precise years are: ...
3
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1answer
48 views

Time Series Forecast: Convert differenced forecast back to before difference level

I am using R and I need an easier way to produce forecasts of data at the original level based on forecasts using differenced data. The situation, in more detail, is this: I am using several ...
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1answer
19 views

simulating two correlated lognormal AR(1) time series

I'd like to simulate 2 correlated lognormal AR1 time series. I have already found this post which is the answer for 2 Normal AR1 time series How to simulate two correlated AR(1) time series? I've ...
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1answer
36 views

Fitting data to a Markov Chain

I am looking for the reference/toolbox/note on how to fit a finite discrete-time Markov Chain to given time series. Ideally, there shall also be criteria of whether the fit is good, and whether ...
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19 views

SVM predictions of timeseries (forex) data are shifted

I am trying to build timeseries prediction SVM (regression variety) for forex data based on lagged close data. And I am using R. Please see the simple code below and resulting graph, using e1071 ...
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0answers
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How to detect GARCH parameters must be updated?

I use a standard GARCH formulation: $$ \hat{\sigma}^2_{t+1} = \omega + \alpha r^2_t + \beta\hat{\sigma}^2_t $$ with $r_t = \sigma_t \varepsilon_t$ in order to have a daily estimate of volatility of ...
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29 views

ARIMAX or Dynamic Regression [closed]

What are the guidelines we should consider when choosing between ARIMAX and Dynamic regression(State Space model)?
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45 views

Predicting an ordered sequence of future events

Please advise on methods and models for prediction of future events sequenced in time based on some previous event history. I need to solve the following problem: Input data: a huge (750 GB) set of ...
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1answer
143 views

Time-series forecasting (in C#)

I'm developing an app in C# (WPF) that amongst other things, it makes a time-series based forecast of sales (4-5 months into the future). I'm an industrial engineer so I'm not pro in statistics nor in ...
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4answers
87 views

Time Series for each customer

Is it possible to create Time Series Analysis for each customer? Say if have 100 customers and I wanted to predict how much amount they are going to spend next. I have done the Time Series for the ...
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52 views

fitting a model for time series data

Folks, I am working on time series traffic data where the waiting times are indexed over time, with 288 observations for 24 hour time period (interval of 5 minutes). I am trying to cleanse the data, ...
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34 views

Mathematical representation of a seasonal ARIMA(1,0,0)(1,0,1)60

I'd like to represent the order of the Seasonal ARIMA(1,0,0)(1,0,1)60 model mathematically. Here is the equation I came up with so far: Eventually, i'd like to represent it as a "conventional" ...
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57 views

R forecast from STL

I want to understand how forecast from STL function in R works. So, I am not giving any reproducible code here. Below is the procedure that I worked on time series I used STL decomposition on my ...
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11 views

Within $R^2$ vs between $R^2$ vs overall $R^2$? [duplicate]

I just ran a fixed-effects regression using the xtreg command in Stata using time-series data and I get 3 different $R^2$s. One is the within $R^2$, the other is the between $R^2$ and the last one is ...
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22 views

Forecasting sales for multiple departments using external factors

I have got the weekly sales information for various locations for about 3 years.It has got information for 157 weeks.Also,I have got the probable external factors affecting the sales.I want to ...
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1answer
92 views

How to understand this ACF

I have two time series. After calculating the ACF, they are like the plot below. Does anyone know the meaning of this ACF plot? I know it's non-stationary time series, but I don't know how the ...
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9 views

understanding chart of mean difference comparisons of groups over time

I am trying to understand a study which reports changes over time in the DSES (Daily Spiritual Experiences Scale).The table reports results for both the control group and the intervention group. The ...
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1answer
67 views

generate a time series comprising seasonal, trend and remainder components in R

I want to generate a time series comprising three components: a seasonal component, a trend component and a remainder component. Moreover, I want to be able to chnage the level of trend, seasonality ...
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3answers
66 views

forecast using arima models

I am trying to predict values using arima(0,1,1). After doing predict(mod,n.ahead=5) (in R) am getting the same value for all ...
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20 views

which code to be used for forecasting arima model [migrated]

i am trying to forecast an arima model (0,1,1) in R studio. which function can i used to forecast the model?
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0answers
33 views

Zero p-value for Dickey-Fuller test

I feed sample time series data in statsmodels Dickey-Fuller test, and as a result I get exact 0 (zero) for p-value. I'm not sure how to intrepret that. I think that it doesn't imply stationarity as ...
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1answer
33 views

Estimation of VECM via ML and OLS

Take a vector error correction (VECM) model: $$\;\;\;\Delta y_t=\Pi y_{t-1}+\Gamma_1\Delta y_{t-1}+...+\Gamma_{p-1}\Delta y_{t-(p-1)}+\varepsilon_t$$ where $\Pi=\alpha \beta'$ and each row of ...
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1answer
45 views

Skewed posterior distribution on constrained parameter space for Bayesian inference of MCMC. Advice on what to do?

I am running a fully Bayesian MCMC procedure to estimate some time series models, and my model has a lot of parameter estimates. In particular, one of these parameters, $\phi$, is $\in [-1,1]$. The ...
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2answers
80 views

Why does the density function has product of variance and covariance for higher model order time series

In my previous question Density function for AR model, the density function of AR model has the covariance-variance matrix given as $\sigma^2 *V_p$. In multivariate Gaussian distribution, the pdf ...
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26 views

Holdout MAPEs in SAS PROC ARIMA and SAS Forecast Studio don't match

I have a Time Series (ARIMA) model in SAS, modelled using proc ARIMA which I am trying to replicate in SAS Forecasting Studio. What I see is that The parameter estimates in both are very similar ...
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1answer
20 views

Time series tracking queue optimization problem

In order to track prices of many different products from different sources, I must optimally schedule a group of trackers dedicated to price collection (ie. collect one price at a time for each ...
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0answers
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AR(n) model with exponents

When we discuss a (time-series) model $AR(n) = \Sigma_{i=0}^n Y_{t-i} + \cdots + \epsilon_t$, we use $n$ to refer to the number of time steps back the autoregression includes. In other such models, we ...
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A question about Dickey-Fuller Unit-Root Test

I am reading Dickey-Fuller Unit-Root Test in Time Series Analysis with Applications in R by Cryer and Chan and have trouble understanding some discussion on equation (6.4.1). So they took this ...
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1answer
35 views

How to predict the time series data

I have no background of advanced stats. I am an engineer and I have the following data. I am representing it as a decent graph for better understanding. I want to forecast the collision for the next ...