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

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The results and specifics from the 'qs' function in R

I'm not entirely familiar with the results of the qs() function in R's package seasonal. But, by what I understand roughly, the ...
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51 views

How are outliers dealt with in R after detected? [on hold]

Once outliers in time series are detected in R how exactly are they dealt with before forecasting? I dont want commands to use i would like the method. Please do not give any answers to do with ...
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40 views

Residuals - What are they? How can i obtain them?

So, i have a data set. I decide to fit an AR(1) model to it thus obtaining a model of the form $X_t - \hat{\phi} X_{t-1} = Z_t \quad Z_t$ is $WN(0,\hat{\sigma^2})$ Which in matlab is given by ...
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20 views

Hidden markov model multivariate regression with time-series data

I am working with a dataset that includes the trajectories of various car trips and would like to be able to predict their destinations using only a subset of the trip trajectory. For instance, if in ...
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10 views

On the use of the autocovariance generating function

The autocovariance generating function is defined as: $$g_X(z) = \sum_{h = -\infty}^{\infty} \gamma(h)z^h.$$ Where $\gamma(h)$ is the autocovariance function of the considered process $X$. I can ...
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13 views

Using count data with number of days

I have two populations A and B. The data consists of count data per number of days after an event has occurred. For example: ...
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50 views

How can a univariate seasonal time series be made normally distrubuted by Box-Cox transformation?

I'm trying to fit a sarima model on the univariate data with 180 points (periodicity=12). I use the auto.arima function in R. After fitting a model to the data, the only problem is the violation of ...
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21 views

reference for regime shifting models [migrated]

I'm looking for a good introduction to regime shifting models. It would be nice to see things like simple example of regime shifting models, ways to detect a regime shift in data, fitting regime ...
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22 views

De-normalizing Google Trends data?

Does anybody have suggestions on how to de-normalize Google Trends data? The site says that their trends are made with the following metric: The numbers on the graph reflect how many searches ...
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37 views

How to use a Hidden Markov Model to detect state in a time series?

Questions Am I right in assuming that the emission probabilities will not be following a gaussian distribution for my particular problem? Obviously, I will need to train the model for state ...
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1answer
16 views

How to compare 3D accelerometer data in time series?

I'm trying to find similarity between two time series of 3D accelerometer data: Just by looking at the graphs I can tell that red-circled parts looks pretty similar to me, but I would like to get ...
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16 views

Determining statistical significance of data changing over time

I have collected motion data from three people over two days. Each of the subjects collected motion data from themselves for around 5 hours a day, for the two days, so I have about 10 hours of data in ...
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95 views
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Putting less weight on certain data points in a series for forecasting

I have a data set that contains outliers (big orders) i need to forecast this series taking the outliers into consideration. I already know what the top 11 big orders are so i dont need to detect them ...
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38 views

How to simulate an ARCH / GARCH model in R? [on hold]

Considering a standard form for a ARCH model: How can I replicate the process in R not using the functions such as garchSim? ...
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12 views

ARMA and white noise [on hold]

Let X_t denotes causal and invertible ARMA p,q process, W_t represent white noise 0 sigma^2 INDEPENDENT OF x_t, show that X_t + W_t can be represented as an ARMA a,b process for some a,b
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46 views

Time series and EViews

I have 3 questions on EViews: m, x, and y are three series. I have found that $m \sim I(1)$, and $x \sim I(2)$,and $y \sim I(2)$ Firstly, can I generate first degree difference by writing " d(m) " ...
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77 views

Testing for autocorrelation: Ljung-Box versus Breusch-Godfrey

I am used to seeing Ljung-Box test used quite frequently for testing autocorrelation in raw data or in model residuals. I had nearly forgotten that there is another test for autocorrelation, namely, ...
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21 views

Determining the optimal lookback length for an arima forecast

How can I determine the optimal lookback length for an arima forecast? ...
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39 views
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Assumptions and terminology for dynamic regression with endogenous offset ($y_t=y_{t-1}+\beta X_{t-1}+\epsilon_t$)

I'm dealing with a fairly simple time series regression model with the following basic form: $y_t=y_{t-1}+\beta X_{t-1}+\epsilon_t$ I'm assuming that observations of $y$ are known without error. $X$ ...
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8 views

fportfolio package in R [on hold]

I have been trying to use some of the rolling efficient frontier functions (in package fPortfolio) but I need to feed them with ...
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15 views

Does downsampling affect trend

I have a large set of time series data for which I want to identify the trend. For trend identification I am using a Simple Moving Average (SMA) function over my raw data in order to smooth them ...
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1answer
27 views

Prediction intervals in ARIMAX accounting for forecast uncertainty in future $X$?

I have a problem with my SPSS software and ARIMAX forecasts. Consider a series $Y$ that depends on a different series $X$, which is not known in advance with certainty, but must be forecasted itself. ...
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8 views

Maximizing mean reversion of residuals

I'm regressing multiple stationary time series in order to maximize the mean reversion of the residuals. I fitted a model via OLS, and discovered that the residuals had a strong negative ...
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25 views

Modeling different lag structures

I know there are various information criteria that can be used to compare model specifications, including those with different lag structures. I can easily compare the Akaike Information Criterion ...
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23 views

Describing trend magnitude or detecting trends

I have time series data. One observation per time period, about 10 observations or so. When describing the data (I am interested in descriptive statistics), I'd like to say that there is either a ...
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27 views

Comparing two algorithms by time series analysis

I have two algorithms. There is one vector of accuracy measurements for each algorithm. Each accuracy result in a vector corresponds to a moving average over a sliding time window and the vectors are ...
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16 views

lin- log model with unbalanced time series

I want to compute the following regression: lm(y~x+log(TAF) from observation nr. 100 to observation nr.300, where x is a controll variable. Now the problem is ...
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57 views

Alternative to Pearson correlation test

I want to test the correlation between various timeseries. As far as I can tell, finding the Pearson correlation coefficient is a good way to do this. The results I get, however, are not entirely in ...
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63 views

Constraints on the Coefficients of a Seasonal ARIMA Model (Possible Software Bug ITSM)

I am attempting to fit a seasonal ARIMA models using ITSM software. The following is the model. ARIMA$(1,1,0)\times(1,1,0)_{12}$: $\phi(B) \Phi(B^{12}) = (1-\phi B)(1-\Phi B^{12})=1-\Phi ...
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18 views

Can I take mean of correlation coeficients for equally spaced data sets?

Historic market (Cash) prices and future contract prices are available for last 4 years. I have found correlation between Jan'11 market price with Jan'11,Feb'11 and March'11 future contract prices ...
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24 views

What is the best approach to estimate the differencing order of a FARIMA model?

I am trying to fit a FARIMA model to a monthly discharge time series with long memory properties and forecast it. I have seen two type of approaches: (1) estimate Hurst parameter to find d ...
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10 views

Stability of Time Series Hierarchical Clustering

We have a dataset with six time points and three biological replicates each. Therefore, we have a vector of 18 measurements for each feature, and used hierarchical clustering with Euclidean distance ...
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18 views

Do Difference-In-Differences Estimators Inherently Remove Seasonality?

I have crime data which are known to be seasonal, and I want to determine the effect of a treatment on the crime. I have a treated group and a control group which share similar characteristics. The ...
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54 views

Ideal statistical or machine learning technique to model highly cross-correlated data

I'm trying to build a model that can predict streamflow for an alpine (snowmelt-fed) watershed using snow albedo (roughly, the energy reflectance of the snow) data. Albedo controls the melt of the ...
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10 views

volume and stock price [closed]

I am trying to look at the relationship between option volume and stock price. For this I intend to divide my data into intervals of 5 mins (Link). Though I suspect there will be intervals for which ...
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2answers
35 views

Modelling a nonstationary variable with stationary and nonstatianary variables

I am very confused about time series analysis. Let $y$ is the dependent variable, which has an increasing trend. Let $x1$ is a price index for a group of goods. I know that $x1$ creates the general ...
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9 views

Need help setting up a model and running a test for significance

new poster here. I've taken very basic stats classes so I would like some help setting up a model testing the significance of an Act that was passed by the US gov't recently utilizing real data. ...
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22 views

Exponential smoothing state space model - stationary required?

I came across with the Exponential smoothing state space model for time series forecasting. My question is if it does require that the time series is stationary? Is there any paper that explicitly ...
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10 views

R packages for Durbin-Levinson algorithm and innovation algorithm for time series forecasting [migrated]

I am looking for a package in R that implements the Durbin-Levinson algorithm for time series forecasting in $AR(p)$ model and innovation algorithm for $MA(q)$ and $ARMA(p,q)$ model. I looked at ...
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39 views

Is this the wrong way to do cross-validation?

I am building an ARIMA model and did a grid search to find which values to use for my AR and MA components using the AIC criteria (this was using all of my data). The results are in this graphic: ...
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How can I compute cross-correlation and auto-correlation in R using pooled data?

I'm trying to perform a lagged linear regression on time series data sourced from ~10,000 hospital patients, for the purpose of estimating causal relationships between administration of a drug and a ...
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1answer
20 views

How to check if the data is intermittent or too many zeros are due to seasonality?

I have a dataset for weekly number of calls to a call center for three years.The data is seasonal (I know this from practitioners knowledge) which means that calls normally come on summer and winter. ...
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10 views

Finding correlation of periodic data

I am working on a hedging model for commodity.I have past 36 months data of commodity market price and future contracts price. e.g. on 1st April,2014, market price is x,April contract price = x+1,May ...
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14 views

Growth mixture modeling with latent variables in R with lcmm

I am trying to replicate the analysis that was used to make this figure: I have measured the depression levels (a quantitative variable) in my subjects at the following time points (in months): ...
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21 views

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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1answer
88 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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85 views

Interpreting regression results

I ran the following regression using R. ...
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25 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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132 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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11 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 ...