# Tagged Questions

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

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### Changing sensitivity (cval) in tsoutliers resulting in unexpected results

I am using the excellent tsoutliers R package to detect outliers (additive outliers, temporary changes etc.), but the cval ...
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### Price Prediction for more multiple products

I need to arrive at a guidance value for multiple products (more than 10K) for multiple customers. I am building two segmentation models - customer and product segmentation to suggest the price. On ...
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### Method for analyzing interactions of periodical exposures (drug x drug interaction and likelihood of adverse events)

I am interested in studying drug usage interactions (drug x drug) and its relation to adverse events. I would appreciate help with choosing the right model/method for this type of analysis. The data ...
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### Regression with Dummy Restrictions in Seasonal Factors [duplicate]

this is my data: ...
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### GARCH Modeling Production time series

I'm working on a factory's production data (chronological) and I want to apply GARCH-ARMA Model on it, here is the plot of the data. Is applying GARCH-ARMA a good idea? If so, how do we come to the ...
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### Non-parametric smoothing a small sample time series with fixed/known t(0) and t(n)

I would be grateful for any suggestions on how to smooth a time series with the following properties: We observe $t(i)$ for every integer $i=0...T$. $0 < t(i) < \infty$ $T$ is typically small (...
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### Time Series : Proof of the Moving Average of order 1 model

For those of you who are versed in time series theory, can you help me with this little question ? Can someone explain to me the concept behind the theta and it's properties? Is it a constant ? and ...
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### Relation discovery between two time series data

I'm looking at analyzing the relation between temperature & sales/searhes of particular product at a daily grain The relationship is little complex, for example Sales go up for low temperature ...
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### State space modelling of longitudinal data in r

I have n stations, and for each station there are m time series observations on different days, each of length ...
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### How to measure the impact of a product on the global revenue?

We have products daily revenue and when each product started being sold by the company. We also have different break-down of product revenue by location, store, sales person, etc. We need to measure ...
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### Maximum likelihood estimation for non-stationary time series

I want to estimate how the taxes influence the retail price of alcoholic beverages. The price function is tricky because in EU countries there is excise duty and also VAT. The non-linearity (which is ...
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### Is weakly stationary equivalent to $I(0)$?

I'm currently reading some time series lecture notes. It says that: Weakly stationary (or wide-sense stationary) processes are said to be $I(0)$ (integrated of order $0$). Let's call the above ...
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### Simulating a Stochastic Integral of OU process

The stochastic integral I want to simulate is $$\int_{0}^{1}J_c(s)dJ_c(s)$$ where $J_c(s) = \int_{0}^{s}e^{-c(s-r)}dB(r)$, is an OU process. I simulate the data using Matlab and the sample codes are ...
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### Cycle detection of a time series graph (y axis power) - machine productive cycle vs idle times

I'm fairly new to data analysis so I'm not exactly sure on how to approach this problem. I have obtained data output from an industrial machine which has 2 states - productive and idle. The productive ...
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I have a really small time series dataset (21 yearly observations) and I want to check if my data is stationary. ndiffs(TS, test="adf") ...
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### Statistical analysis of two groups of time series

I am working on an evaluation framework for algorithms applied to video sequences but I'm stuck on how to correctly do the actual evaluation. I'll try to explain my data as best I can, however, my ...
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### LSTM mimicking unseen time series data during testing

I have built a LSTM network which has been trained on a time series dataset (which is week-wise logged). The LSTM is able to make pretty accurate predictions as of now. Training data seems to have ...
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### Reverse-Engineer Time Series Matrix With Machine Learning

I'm trying to figure out the following situation which is almost the same as in this post here Time series with multiple subjects and multiple variables ...
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### Adaptive baseline for time series data for anomaly detection

I would like to create/calculate a dynamic baseline for continues time-series data. The data is arriving in real-time (streaming) every N minutes interval. I googled around and came across control-...
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I tried looking this question up on google and didn't find material that answered my question. But my questions are: (1) Is there a method to determine how long it takes a leading indicator to ...
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### Example of 2 series correlated but not cointegrated and vice versa

I am studying the time series and only kind of understand correlation vs cointegration. Can someone provide an example of two series that are correlated but not cointegrated, and two that are ...
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### Intuitive explanation of state space models

Having looked into options for modelling and forecasting a financial time series based on mixed frequency data, I came across state space models, which seems worth exploring. I've however been ...
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### choosing test set in a seasonal time series

The data is sequential, but not necessarily continuous, ie. there are multiple gaps between the start and end date. I fit a regression model, which may or may not involve lagged variables, and I want ...
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### How to select the length of a time series when fitting models for prediction

Let say that one wants to fit a model to a daily financial time series for prediction (e.g. ARIMA, SVM). If data are stationary, ideally the longer the time series, the better. In practice, I don't ...
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### When is time treated as a discrete variable?

Time is usually treated as a continuous variable but in some cases it is discrete. An example would be with a drug study and measurements are taken at 1, 2 and 3 hours. Am I right to think an ...
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### Repeated measures MANOVA for testing difference among multivariate time series?

I measured behavioural multivariate time series (3 variables) from 7 dyads performing an experimental task. For each dyad, I have a multivariate time series (that is, I don't have data from each ...
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### Can Random Forest regression handle non-stationary input variables?

I am working on a project where the explanatory variables include soil attributes, land use and land cover properties, stream flow and climate (precipitation, temperature etc) measurements recorded at ...
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### How to correct a variable for unit root?

So I have done my dickey fuller test on the variable exchange rate. The result table indicated that I do have unit. In addition, I have tried lagging the variable but still ended with a result that ...
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### When would the data set be stationary?

I am not a statistician or mathematician and I need some help. I did three experiments as I labeled on the figure, 3,4,5, each experiment has x and y results. The markers are the real data and the ...
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### Forecasting with mixed frequency data

Just a general question that I couldn't find too much on. What would be some good approaches to one step ahead forecasting of financial time series with mixed frequencies? Often a lot of the ...
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### Why unit root test with D-F not using normal or t test?

Let $X_1, \dots , X_n$ be observations from the AR(1) model. For large $n$, the maximum likelihood estimator $M(\phi_1)$ of $\phi_1$ is approximately normally distributed as $N(\phi_1, (1−\phi_2)/n)$...
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### What is the approporiate test?

I have two variables ; First variable is ordinal and it represent years series from 2006 to 2015 and another variable which is interview score and I want to study if there a relationship between the ...
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### Would including “year” as a categorical random effect remove a long-term trend in a mixed effects model?

I am trying to detect evidence of warming in a monthly temperature time series over a 20-year period by testing for a trend. I have precisely followed the method of Crawley (2013) The R Book, 2nd ...
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### What is the probability of the first positive event in an sequence of binary events where sequences have finite but random lengths?

I have a time series of observations from a longitudinal study of individual objects. These observations are seen as discrete sequences of features, one sequence per object. The sequences have ...
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### Is this uncertainty representation correct?

I have a set of execution times for some processes. But there is uncertainty in these values. I call this $$ET + \lambda ET$$, where $\lambda ET$ is the delay. I sample $\lambda$ from a gamma ...
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### FInding relevant features for a time series segmentation

I have a time series data, where each of the data point belongs to one of the known clusters. What I am interested is to perform a HMM so that we can obtain hidden states that further abstracts out ...
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### hts in R: Convert data.frame into a gts object [closed]

I'm a month-old user of RStudio. Currently, I'm working with hierarchical time series analysis with the hts package. After reading my .csv data below, ...
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### Time series with slightly unequal intervals

I'm very new to statistics, and I have a problem that may or may not exactly be considered a time series analysis problem. I have a large set of vehicle location measurements (x0, y0)...(xt, yt) taken ...
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### Methods for time-series pattern weightings in machine learning

I am currently developing an anomaly detection algorithm to test for anomalies in system usage. This is obviously very seasonal in nature (for example, during the Super Bowl, for example, there will ...
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### Across time correlation

I got two data sets (different omics data) from several observations across time (Two data sets will look like N*P1*T, N*P2*T, N=number of observations, P1/2=number of variables of first/second omics ...
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### Adding together ARIMA forecasts vs an aggregated model?

Say I am forecasting sales for a company that has four regions using ARIMA models. Each region behaves a little differently so four different ARIMA models are used. In order to forecast overall ...
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### What's the best way to compute the offset of a time series?

Say that I have a signal $f(t)$ composed of an offset, another signal and noise: $$f(t) = offset + g(t) + \epsilon(t)$$ The function $g(t)$ is strictly possitive but the epsilon can make the ...
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### Sliding window and historical data

In my problem I have a longer period of historical data of a time series. I need to predict for some specific points in time in the future. For these points in time five previous values are also ...
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### Difference between first one-step ahead forecast and first forecast from fitted model

I'm doing some time series modeling using R and the forecast package, and found a minor difference I couldn't figure out. I'll reproduce my steps below. First, I ...
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### How to analyze differences between two time series collected under two different conditions

How should one analyze time series data that were collected during two seasons: season 1 and then at season 2, where during each season a measurement sample for several continuous variables were ...
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### Making a time series prediction for events per second based on past data

I have data values for events per second (EPS) present in log files pertaining to various devices. The idea is that these values should help us observe a trend and create thresholds for specific times ...
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### How are errors terms calculated in GARCH model by rugarch package?

I am fitting a GARCH(1,1) model to the data and want to look at the innovation distribution. ...
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### Book about time series analysis in Stata

Does somebody know a good book which outlines the time series analysis in Stata, that is, the various commands explained. I am aware of the Stata manuals; however, they are not that user friendly for ...