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

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Generating randomized time series from discontinues historical data

I have some historical data from microbiological sampling, which are not collected continuously. For example historical data are in 2008/01/12, 2008/03/25, 2008/5/30, 2009/07/05, 2009/07/29.For ...
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82 views

Testing if frequency of event occurrences over week days is uniform

I’m trying to figure out if there’s a calculation that can be done to show you have enough data to draw conclusions on trends within the data set. I have made an observation on a class of equipment ...
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63 views

How to take advantage of multiples series with the same behaviour for forecasting?

I'm quite new to statistics and forecasting, and I have to build a model to forecast monthly sales of different related products in a bunch of cities. Seasonal ARIMA seams to be a good model for ...
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15 views

How is GARCH's p estimated in software?

From what I know, the GARCH(p,q) model is estimated via MLE and through an iterative process. Let's say if i wanted to recreate a GARCH(1,1) parameter estimation with excel solver (through maximizing ...
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27 views

what is a stationary process?

I just started learning time series and this notation confuses me. For a ARMA process, phi(B)X=theta(B)Z according to some notes I found online, the criteria for the process to be causal is where ...
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119 views

How to use Pearson correlation correctly with time series

I have 2 time-series (both smooth) that I would like to cross-correlate to see how correlated they are. I intend to use the Pearson correlation coefficient. Is this appropriate? My second question ...
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27 views

How can I predict based on several time series of many different projects?

I want to predict the time that a client takes to pay for a service that has already been received. We are talking about a construction company, so the payments are always overdue since the company ...
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1answer
47 views

Comparing Time Series Forecast Models

I'm to write a short report on Time Series forecast comparison. I'm a beginner in the field. I want to investigate how one chooses which model is better than the other based on the forecast results. ...
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9 views

Bisecting K-mediods [duplicate]

Is there an algorithm like Bisecting K-mediods and what would its advantages/weaknesses be? It seems to me that it could be used well in combination of Dynamic Time Warping for clustering time ...
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92 views

Why is the arima function giving odd answers

I have a problem in interpreting what the arima function in R is doing. I have the following code: ...
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1answer
58 views

modelling time as continuous vs. discrete

I am writing an analysis plan for data that is collected on approximately 30 people at approximately 5 unevenly spaced time points. I am planning to analyze the data via a repeated measures mixed ...
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63 views

Time-series regression

Suppose that a typical firm determines its level of stocks $H_t$, in accordance with the following rule: $H_t - H_{t-1} = \lambda (H^*_t - H_{t-1}) + \epsilon _t$ where $\epsilon _t$ is a serially ...
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15 views

Continuous predictor of a significant difference on another scale at T1 and T2

I was wondering if anybody could point me in the right direction for a statistical test. I’m looking whether a continous variable (e.g. a personality variable) predicts a significant difference ...
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36 views

Predicting university course marks using historic data of class mean and student's own marks

I would like to predict my course marks for this year based on the data for class mean and my own marks for the past years. What would be a good starting point for a model for such kind of data? ...
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1answer
91 views

ARIMA equation interpretation

I'm trying to replicate ARIMA (1,0,1)(1,0,1) equation in excel as a formula but I am not able to understand the interpretation of white noise residual e(t) or u(t).If could help me understand the ...
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35 views

Visually representing confidence and standard deviation in a time series

We've been tasked with presenting a time-series graph showing 2 series of estimations each with a standard deviation and confidence. There are only 4-5 points in each series and both occur over the ...
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13 views

Change in distribution of a portfolio of customers

I'm looking for some high-level thoughts on understanding a change in distribution for a portfolio of customers. I have a file with information on a bunch of customers. These customers are purchasing ...
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1answer
26 views

Smoothing intraday data when only looking at a certain time range

I have an intraday price series (5 minute) over several months. I want to smooth the data using an ema but also i am only interested in analysing the series between certain time periods eg between 8am ...
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1answer
87 views

Why is the Confidence Interval Changing for this Time-Series

I have some R code (which I did not write) and which performs some state space analysis on some time-series. The data itself is shown as dots (scatter plot) and the Kalman filtered and smoothed state ...
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39 views

Fourier vs ARIMA vs Factor analysis vs PCA?

Background I'm currently analysing a timeseries. My data consists of half hourly observations of a certain measurement. This data is human generated, and so we believe there will be daily, or weekly, ...
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27 views

Can Intervention analysis be used to forecast time series

if I have an estimate of the intervention variable from a similarly interrupted time series can it be used to forecast another similar time series after the effect of intervention. For example lets ...
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1answer
83 views

Review of Box-Jenkins methodology

i just finished developing an ARMAX model with python (mostly statsmodels) in order to forecast some data. My next step is to test the data (24 time series) with the given ARMAX model. As i need to ...
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2answers
130 views

Dynamic Time Warping Clustering

What would be the approach to use Dynamic Time Warping to perform clustering of time series? I have read about DTW as a way to find similarity between two time series, while they could be shifted in ...
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30 views

Automatic selection of lowest information criterion comes with warning

I am building a forecasting model (ARMA) and found the very useful code-object arma_order_select_ic(see code below). It all works, however, each calculation comes ...
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47 views

Vector Autoregression - Model Selection in R

I have 50 time series and I'd like to form a VAR equation for each of the time series. I'm looking for a method to find the best subset required for each time series VAR equation. For instance only ...
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2answers
94 views

What exactly is Box-Jenkins method for ARIMA process

The Wikipedia page says that Box Jenkins is a method of fitting an ARIMA model to a time series. Now, if I want to fit an ARIMA model to a time series, I will open up SAS, call proc ARIMA , supply the ...
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41 views

Analyzing relationships between ordinal and continuous time series data

I have two sets of time series data - roleTrajectories & normalizedDegree. The former data set contains ordinal rankings of subjects' positions within a network at 13 time periods. The latter data ...
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31 views

Standardizing vs differencing to remove non stationarity

To remove non stationarity in a time series, we can standardize the time series by subtracting the mean and dividing by the standard deviation. We can also keep differencing the time series until the ...
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39 views

Does a seasonal time series imply a stationary or a non stationary time series

If I have a time series that has got seasonality, does that automatically make the series non stationary? My intuition (probably off) is that it does not. Seasonality means that the series goes up ...
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1answer
101 views

forecasting time series based on previous value forecasted

I'm working on time series with a monthly demand for 5 years. Currently, I'm using naive method to forecast 12 months (h=12)and it does work very well I want to forecast only for one month (h=1) ...
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60 views

Does stationarity under ADF test imply mean, variance and covariance stationary?

Newbie question. I am reading about stationary series and understand that it has many forms: mean stationary variance stationary covariance stationary If I run an augmented dicky fuller test and ...
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25 views

What is the ‘Pile-up Problem’?

In methods of trend-cycle decomposition, what is meant by the 'pile up problem'? How can the pile up problem be detected? Can it be detected by the method of visual inspection? If so, what are the ...
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31 views

Basic - Modelling Two Series, one is an index

I'm trying to model two time series. One is a seasonally adjusted # of new jobs number against and index of business development. Its been a long time since I took econometrics, so I'm hoping ...
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24 views

Different values predicted by OLS model and Time Series model

Let us say , I have an explanatory variable X and a dependent variable Y and I use OLS and find Y = 0.5 + 3X. Now let us assume that both X and Y are time series data, so using ARIMA modelling ...
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28 views

System identification, machine learning and time series

I have recently become a bit familiar with the machine learning techniques, and examples of problems where they are ought to be applied. For example, we can try deriving models for the time series or ...
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49 views

How many times can one difference time series data? [closed]

I am going to work on the impact of taxation on economic growth and I want to use VAR model and Stata software. What I want to ask is I have three types of taxes in my country, direct domestic tax, ...
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1answer
70 views

Why should we remove seasonality from a time series?

While working with time series, we sometimes detect and remove seasonality using spectral analysis. I am a real beginner in time series, and I am confused why one would want to remove seasonality from ...
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1answer
48 views

How to Determine whether Simulation Draws are Correct

I have implemented algorithm 1 and 2 in this paper http://www.lse.ac.uk/statistics/documents/researchreport61.pdf for the analysis/simulation hidden states for some time series. The reason why I am ...
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49 views

How do I compare date-ranges from a time series?

I have a time series which contains monthly readings for air pollution in a city. The seasonality from this time series has been removed. Given two date ranges, for example Jan-Aug 2008 and Jan-Aug ...
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Forecasting Using the xreg parameter in forecast.gts with several external variables with different values per each time series (hts package) [migrated]

I'm currently using the forecast.gts (hts package) with a single external variable that hold the same values for all individual time series in order to create a 30 ...
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1answer
103 views

Test for cointegration between two time series using Engle–Granger two-step method

I am seeking to test for cointegration between two time series. Both series have weekly data spanning ~3 years. I am trying to do the Engle-Granger Two Step Method. My order of operations follows. ...
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36 views

Dummy for multivariate time series regression (intercept and slope effect)

I am trying to understand if it is possible to use dummy observations in time series analysis, to split the effect of two or more groups in the model. Assume that we have n observations for 4 ...
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19 views

Time series comparisons: early detection of mismatching series after n points for efficiency

I am doing time series comparisons. I have a set of values (my query set Q) that I need to compare against many other reference sets (R), each of which contains the same number of values as my query ...
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1answer
73 views

Does dummy interention variable (pulse or step) must be differenced when it is added to ARIMA model?

I have read some opinions from this forum and from other sources that when the dependent variable in any from of ARIMA model (whether ARIMA errors, ARIMAX or transfer function)is differenced, you ...
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1answer
81 views

How to “undifference” a time series variable

I need to "undifference" or "integrate" a time series variable. In its current state, it is twice-differenced (a money market, cash return proxy variable that was I(2) to achieve stationarity). I ...
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3answers
102 views

Decompose a time series into superposition of step functions?

Background I have time series data comprising hourly observations of a sensor's readings over a period of almost a year. The sensor records an environment whose baseline measurements should have ...
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1answer
62 views

Which distribution to choose when modeling variance of a normal distribution?

I have a simple time series model where there is a single hidden variable $\lambda_t$ which changes over time: $\lambda_{t+1} \sim \mathcal{N}(\lambda_t,\sigma)$. The $\lambda_t$ is then used as a ...
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5 views

Rolling window in time (t) to compute forecasting [migrated]

I want predict using Recursive Method. Each month (t) i need to roll my data window regarding the last month, one month ahead (t+1) ...
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75 views

“Future-independent” smoothing methods (as exponential smoothing)

I'm searching for time series smoothing algorithms, which give "future-independent" results - each next smoothed value depends only on previous data (smoothed or not smoothed), but not on any future ...
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If peak was higher than normal, why does updated arima model overestimate activity in remaining time series?

I have a number of time series with strong seasonality and I am using auto.arima() from R's Forecast package along with Fourier and dummy/explanatory variables to address the seasonality to make ...