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

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CausalImpact - Should I use more than one control?

In the intro document (https://google.github.io/CausalImpact/CausalImpact.html) it suggests that using one predictor is not ideal. Am I current in understand that they mean one control? If so, should ...
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5 views

Extrapolate Multiple Time-series to Null

Given at least two time-series each associated with an index (that correlates with the differences between time-series), is there an established method to extrapolate a new time-series based on the ...
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1answer
25 views

Appropriate predictive model for two random time series with serial correlation

Say I have annual observations of the temperatures at the North Pole and South Pole for many years. I want to build a model that given the South Pole temperature for the current year and all prior ...
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0answers
12 views

How do we understand when a time series must be decomposed or normalized?

Why do we use decomposition in time series? How much information will be lost if we will delete (decompose) the seasonal component? Where I can find some documentation which describe what time series ...
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20 views

Comparing similarities and differences of time series data

how to compare the shape of two time series data. E.g. comparing fluctuations of two time series data. like, how to quantify whether one is more fluctuating than the other?
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0answers
11 views

Option daily “Open Interest” data used for liquidity study(comparison on conversion from american to european style option).

Can somwbody suggest if I can use paired sample t-test in studying the daily average open interest data for 15 stocks using paired sample t-test. I have checked the normality with respect to the ...
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0answers
24 views

Granger Causality and Regression

I have an enquiry regarding the Granger Causality analysis. It is said that it is performed to check whether “X causes Y”, or to put it differently, whether X contains any predictive information with ...
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0answers
8 views

Gap-filling biophysical sensor time series

I am exploring imputation methods for filling gaps in time series from multiple co-located biophysical sensors. At a given site, we have about 25 sensors measuring things like temperature, humidity, ...
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10 views

Two-period lagged effect on dependent variable due to increase in independent variable

The following time-series is given: yt = 53 + 0.4xt + 0.2xt-1 + 0.1xt-2 + 0.8yt-1 where t denotes the time period. If the is a one-time increase in x with 100 in t, what is the effect on y in period ...
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0answers
22 views

Calculating probability of sale from auction data

I have some data representing the last 6 months of closed auction data from a particular website. The data I have includes market value of product, actual sale amount, and date sold. I have about 600 ...
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1answer
39 views

How to identify the seasonality of a timeseries from the Periodogram?

I need to identify seasonality/ periodicity of a dataset so as to develop an ARMAX model. This is what the original time-series looks like I have plotted the periodogram of the dataset. Ps: I used ...
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0answers
44 views

Train neural network for forecasting

I am trying to use time series neural network to predict future values. I have time series data from 2010-2014 and I need to predict the values from 2015-2020 using time series neural network. I am ...
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26 views

Unit root test results not stationary, can I apply VAR?

I am working on my project methodology, and I am planning to use VAR model. In order to proceed with VAR, I run my data thru unit root test in Stata, and found that my data is not stationary. Can I ...
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0answers
22 views

PMML and time-series

What is the purpose for embedding the original and predicted time series in PMML models (http://www.dmg.org/v4-1/TimeSeriesModel.html)? I don't understand how these embedded series are being used by ...
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0answers
17 views

How can I intepret and compare ARIMAs from different data sets?

I have human chromosome data. I have 23 chromosomes that consist of equally spaced windows of 100,000 base pairs with a dependent variable attached. I am treating this like a 1 dimensional spatial ...
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0answers
26 views

Newey-West vs Cochrane-Orcutt

I have time series of 189 observations and I want to regress $y$ on $x$. My modeling procedure is the following: I run an OLS and I get the constant significant and b not significant (but I know ...
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0answers
9 views

How to include seasonality in the data ARMAX model that has multiple periodicities?

I am doing regression with ARIMA errors. The residuals are as shown in the figure below. Clearly, the scatter plot shows that this time series has some sort of periodicity or seasonality, but its very ...
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1answer
28 views

comparing ARIMA and AR with external regressor

Consider the following models fitted to the same time series: ARIMA(0,1,1) ARIMA(1,0,0) (that is, AR(1)) with an external regressor Can I use the AIC (or any other information criteria) to decide ...
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1answer
34 views

ARIMA modeling white noise probabilities vs. residual autocorrelation/PACF

I have moderate understanding of statistics and time series analysis. I trying to forecast a weekly time series with lots of outliers and trend shifts. After correcting all of the outliers, I'm left ...
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11 views

Measure changes between the first and last point in a series of data

I'm unable to figure out what the common practice is for measuring changes across a selection of points in a time series, not just the difference of the first and last points. For instance, let us ...
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0answers
12 views

Time series forecasting using ANN

I have an array of data recorded from vibration analysis of a bearing.I want to know how to forecast 30 day later. I don't know machine learning and I'm not so familiar with neural network for example ...
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0answers
29 views

Modeling time series binary data in R

I have time series binary data with other explanatory variables (qualitative and quantitative). I would like to see pattern of events over the time, and influences of different variables using R. I am ...
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25 views

Clarification in the differences between several time-series analysis models

Can anybody give me a simple explanation of the differences among the following: ARIMAX model Regression with ARIMA errors Transfer function model Please provide some references if you can.
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33 views

How to interpret the following Baysian time series representation (picture attached)

I am trying to understand this paper on Bayesian Hierarchial model (http://www.umac.mo/fba/irer/papers/past/vol13n1_pdf/01.pdf) in which one of the sub-models is a time series with random-walk ...
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23 views

Comparing / “correlating” time series

Say I have three time series $X_t$, $Y_t$ and $Z_t$ and from the phenomena I'm observing we can be sure that $X_t$ is _caused_$\,$ by at least $Y_t$ and $W_t$ (there might be other processes that ...
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16 views

Model for irregular time series

I recently started working with regularly sampled time series, i.e. evenly spaced time series. However, I would like to move to irregular time series, i.e. unevenly sampled time series. I have looked ...
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1answer
87 views

Multiple ARIMA models fit data well. How to determine order? Correct approach?

I've got two time series (parameters of a model for males and females) and aim to identify an appropriate ARIMA model in order to make forecasts. My time series looks like: The plot and the ACF ...
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1answer
34 views

how to read time series data? Horizontally or vertically?

Sorry for this stupid question, currently I'm reading "Times series analysis and forecast by example", the data given in the appendix is just a bunch of numbers in a table, do the time series read ...
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42 views

Relation between AR(1) and Vasicek model

The discrete time version of a Vasicek model is equivalent to an AR(1) model with opportunely chosen parameters, as showed in this paper: http://www.damianobrigo.it/toolboxweb.pdf. Following this ...
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1answer
121 views

Understand order of time series

I am trying to build a time series model. I looked at the ACF/PACF and adf test of the series and thought that an ARMA(p,q) model will be suitable for the data. However when I run auto.arima(), it's ...
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1answer
67 views

Unit root near unit circle or near 1?

According to slide 6 of Bartlett's Introduction to Time Series Analysis, Lecture 6 (with emphasis on slide 6), an autoregressive time series model is stationary if the autoregressive polynomial has a ...
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1answer
32 views

Is there a relationship between these two standard deviations

I just started thinking when you have time series data and was curious about the following question. Suppose you have the standard deviation of one observed result. Would the standard deviation of the ...
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1answer
97 views

Correct name for waterfall chart with data point pairs showing net value per pair?

The chart illustrated below is an attempt to show a concept I'm looking to visualize. On each day I have two numbers I want to show - an increase (tasks assigned), and a decrease (tasks completed). I ...
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15 views

How can I filter marketing campaigns out of my decomposed seasonal data?

I've recently jumped into the deep end of statistical analysis of revenue. I've learned a ton about statistics, probability, decomposition (stl), and the Python and R languages. I feel like I'm ...
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1answer
61 views

My project work is on time series using the ARMA model or the ARIMA model

My project work is on time series using the ARMA model or the ARIMA model. Where do I start to analyze my data?..... it is a federal road safety commision data from 2003-2014
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12 views

Time Series - Moving Average without the most recent data

If I understand correctly, I need some recent data to do the time series such as moving average. Jan 10 Feb 20 Mar 15 Apr So the estimation for April will be (10+20+15)/3 = 15 But Now I don't ...
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13 views

Summarizing output of moving correlation

I have 2 yearly time series (of 55 observations each) and I have calculated moving correlations between them (using windows of length 5 years). My aim is to summarize all the correlations I got into ...
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0answers
20 views

Hurst Exponent way off?

In RStudio, I use hurstexp() to gather the 5 estimations for the Hurst exponent. Using the recent 500 days of the VIX index (a highly, highly mean reverting series) ...
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0answers
27 views

Cross- correlation between two non-stationary time series

I have two time series that are growing together. I want to measure if these series are growing similarly together with some lag. Originally, I was thinking I would just take the cross-correlation ...
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1answer
32 views

Visualizing the trend of monthly change in a times-series year-over-year

I am interested in a better way to plot monthly changes in a time-series. Especially I'd like to compare how the monthly change this year differs from the monthly change last year. Monthly change is ...
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1answer
44 views

Trend shifts in timeseries

How can we detect trend shifts in time series? I know of Ets in R which tries to make trigonometric analysis of seasonal data. However I have not found yet a way of finding periodic trend shifts in ...
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0answers
13 views

How to interpret Realized Volatility and TSRV using R

I am looking at some high frequency data and I would like to know how to interpret and compare Realized volatility (RV) and Two Scale Realized Volatility (TSRV). References below. Given X is the log ...
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0answers
7 views

Does it make sense to interpret autocorrelation and box test on 5 data points?

I am trying to see if after I trade a stock the price movements at 2, 5, 7, 10, 30 and 60 seconds after exhibit any autocorrelation. Below I have the returns from my trade price to the trade 2,5,7,10 ...
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4answers
167 views

How to detect abnormality in an otherwise very systematic and regular time-series data for temperature measurement?

I have time-series data, let's say a pandas series, with time (sampling frequency is hourly) as its index and temperature measurement across that time. I want some statistical/time-series principle ...
3
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1answer
37 views

Forecasting monthly time series with known periodicity and a known driver

For 2004-2014, I have monthly measurements of my outcome of interest - some kind of physical exposure - for a collective of many thousand persons. The main determinant for the average exposure level ...
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1answer
14 views

Cross-applying known seasonality adjustment to new data

I have two sets of data, drawn from the same source. I know that the data exhibits seasonal behavior, visible over each week and over each day, and am willing to assume that the seasonal behavior is ...
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1answer
31 views

Does the Dickey-Fuller test for a Random Walk?

Is it valid to say that the Dickey-Fuller test, tests for a random walk? Since the AR(1) process $Y_{t} = \rho Y_{t-1} + e_{t}$ with $\rho = 1$ is the same as the random walk. (Next value is maximum ...
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derivation of equation 2.3 in Baille paper

I'm reading a time series/prediction paper and it's has a result on the first page (equation 2.3) and then more details on how the result is derived are given in the Appendix A. Unfortunately, the ...
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1answer
44 views

Time Series Regression using dummy variables and fpp package

I want to solve the first exercice of the Multiple Regression Chapter of R. Hyndman's online book on Time Series Forecasting (see https://www.otexts.org/fpp/5/8). I use ...
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1answer
76 views

Decomposition of daily time series (several years) with multiple seasonal patterns

i have a daily time series of several years. Graph & CSV-file So far i could figure out with an based on an acf graph and this method: timeSeriesObj = ts(x,start=c(1999,1,1),frequency=7) ...