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

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How to analyze multiple variable time series - suggest references

I have multiple environmental time series variables (for example: temperature, dissolved oxygen, conductivity, depth) measured every few minutes for several months. The variables are measured at ...
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32 views

Reducing high dimensionality as well as feature selection on multivariate time series

Lately I've been reading a lot about time series clustering as I want to search for similar patterns in my own data set. Even though I feel like I understand the basic concepts of this task I still ...
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1answer
24 views

Confidence Interval Application to a time series

So I'm not sure if I 100% grasp confidence intervals. Say I have a huge data set of a bond prices from 1996 to present in MINUTES. Suppose I separate each data by day. If I were to use a Dickey Fuller ...
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22 views

Predicting the missing data out of three values in each of the two vectors [duplicate]

I have 2 vectors of rural and urban populations of the same country. (years from 1975 to 2020) with only three values (1980, 1990 and 2001 years) in each. And I need to predict the missing data. My ...
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1answer
33 views

Predicting on data consisting of many independent short time series?

I have a dataset which contains many (hundreds) of short (3-30 obs) timeseries of different lengths. Each series is currently represented as a number indicating how long it took to the next event. To ...
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31 views

Creating classification features from wavelet transformed time series

I'm interested in using a wavelet transform, Haar for example, to create classification variables from time series data to use in logistic regression. Simple example. Let's say I'm trying to predict ...
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2answers
237 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
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2answers
24 views

Can time be squared to develop a curvilinear model of crop yield against time?

I am developing a linear model of yield against time (33 years of yield data) where year is 1975,1976....2007. I want to know whether change in yield over time was linear or not. So I fitted a linear ...
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1answer
40 views

How can I detect spurious regressions results?

I run bivariate Granger-causality regressions. Let $y_{t}$ and $x_{t}$ be stationary time series. I test if $x_{t}$ can forecast $y_{t}$ with the following regression: $$y_{t+1} = \alpha + ...
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1answer
32 views

Measure accuracy of Holt-Winters model

I'm really confused about measuring the accuracy of Holt-Winters fitted models applying different transformations. How do i compare the accuracy between models when i apply no transformation to the ...
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1answer
90 views

What econometric model to forecast a seasonal commodity demand while incorporating exogenous Information?

I have a monthly commodity demand and try to forecast this series for the next 5 years. Here is a plot: Of course, the natural approach to forecast this seasonality would be some kind exponential ...
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51 views

What is the minimum number of data points required to use ARIMA(p,d,q)?

I'm using the $\mathrm{ARIMA}$$(p,d,q)$ model to predict future time series data in R (see also R's ARIMA documentation). Q: What is the minimum the number of data points we must have in the time ...
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1answer
112 views

Can First Differencing Cause Negative Serial Correlation

Ex. series, say stock prices 103 101 102 150 101 102 100 First differenced 2 1 48 -49 1 -2 Notice you could guess a very large negative number following the very large positive in the first ...
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50 views

Mixing two linear regression models

In time series analysis, I have one predictor $X_1$ that has a higher $R^2$ when regressed against $Y$ sampled at 10 minutes interval. Another predictor $X_2$ has a lower error when fitted against $Y$ ...
2
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1answer
54 views

Show Regression with Arima Errors Equivalent Form of Differenced Variables

How can you show that the regression $y_{t}=\beta_0 + \beta_1x_{t}+\eta_t$ where $\eta_t$ is arima(1,1,1) is equivalent to $y'_t = \beta_1x'_{t}+\eta'_t$ where $\eta'_t=\phi_1\eta'_{t-1}+e_t$ and $'$ ...
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1answer
69 views

Analysis of spatial data over time and space

I have a data set having year-wise monthly average of minimum and maximum temperatures of 32 stations around the country since 1948. The latitude and longitude of the stations are given as well. I ...
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13 views

Error running optim function with STAR from book example

I'm running an example of Smooth Transition AR (STAR) Model from the book "Analysis of financial time series, 3rd edition" by Tsay, in section 4.1.3. The script is as follows: ...
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1answer
61 views

Rolling Window Forecasts in R [duplicate]

I have a question: how do I use rolling window forecasts in R: I have 2 datasets: monthly data which I downloaded from Google. monthly data I downloaded from the CBS (central bureau of statistics ...
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1answer
12 views

Combine results with different veracity

I have 3 neural networks processing 3 different vectors of values. Each NN processes a sample of it's vector and gives binary result (y/n) that is correct with given probability. All 3 NNs give answer ...
2
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1answer
39 views

Which clustering technique to use for a temporal dataset?

I have seen a similar question but thought I'd ask my own to hopefully garner some usefull feedback. Basically, I have a large temporal dataset, consisting of domestic smart energy meter use ...
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1answer
54 views

Forecasting a time series with weights

I'd like to forecast (or predict) a time series with weights. The following works using the regular linear modelling techniques ...
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1answer
43 views

How to perform seasonal adjustment to a time series?

Assume following data set representing each month of the year 2013 with the corresponding consumption of natrual gas to heat my flat and the respective mean temperature. How can I seasonal ...
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19 views

How to correctly concatenate time series data

I have this shifted time series data. For one set consists of features from week1-5 and labels at week6. Another set features from week2-6 and labels and week7 and so on. I have like four sets of ...
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1answer
31 views

Looking for definition: Granger Causality with a common explanatory process

I am looking for help in defining my problem. Essentially, I have two data processes (both continuous macroeconomic variables: $x$ and $y$). There is evidence of bidirectional causality between $x$ ...
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1answer
72 views

Additive vs Multiplicative decomposition

My question is a really simple one but those are the ones that really get me :) I don't really know how to evaluate if a specific time series is to be decomposed using an additive or a multiplicative ...
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1answer
46 views

Timeseries: Find points deviating from the mean

I haven't done much time-series modelling at all and now I have a dataset which screams "time series" at me and now I am hunting for a model. The data: Imagine a video watched by ~400 people, 100 ...
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61 views

Method for detecting anomalies in timeseries?

I am exploring creating alerts for anomalies in a timeseries. Say that I have a graph like this: There are two anomalies here that I would wanted to be alerted on: First, on April 7th with there ...
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2answers
63 views

Test whether there is a significant difference between two groups

I have some trouble with the last test I need to perform for my bachelor thesis. I have two variables and I need to test whether there is a significant difference. The first variable has all the ...
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82 views

Anderson-Darling test in 2D time series

Suppose two time series (of light flux). The goal is to determine whether the series are from the same distribution. It is usual to use the Kolmogorov-Smirnov (KS) test in this situation. However, ...
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26 views

restricting range of values for AR(1) process

We have a stationary AR(1) process defined as $A_{t}= d+ \rho A_{t-1}+ \epsilon_{t}$ with $d>0$; $-1<\rho<1$; $\epsilon_{t}$ is white noise and follows $N(0,\sigma^2)$. What conditions do we ...
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64 views

Test if advertising raised sales?

I have an (offline) advertising campaign that I'm running in one city. I'm trying to figure out how to answer the following questions: What are the chances that the advertising campaign has no ...
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33 views

Estimating a first order plus dead time model

The data generating process is given by the following differential equation: $y(t) = a + b u(t - \theta) + c \frac {dy} {dt}$ Now imagine having as data a long time series for both $y$ and $u$. If ...
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14 views

Dynamic time warping between more than two sequences

Dynamic time warping is a technique to find an optimal alignment between two given sequences. Is there a technique to find an optimal alignment between more than two sequences? Does it as an ...
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1answer
39 views

Is it true that values of parameters do not vary from sample to sample?

This is something I was told. However, it seems to me that parameters of a population can be functions of time, in certain situations, in which case the values of parameters could vary from sample ...
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1answer
70 views

Why could mean centering change results

I used centering for my variables due to multicolleanirity and surprisingly the results (from before to after centering) changed for two interacted variables; one from significantly negative to ...
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174 views

Consequences of modeling a non-stationary process using ARMA?

I understand we should use ARIMA for modelling a non-stationary time series. Also, everything I read says ARMA should only be used for stationary time series. What I'm trying to understand is, what ...
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33 views

Testing significance of correlation between two autocorrelated series

Say I collected the shin bones of N different skeletons; they are all around 30cm long, and I measured different properties P1, P2, P3, P4 and P5 along these bones every 3mm (so I have 100 data points ...
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48 views

Is the Moving Average of ARMA the same of Moving Average of Stock Market?

I'm studying time series prediction and I have some questions. Is the Moving Averages movel studied the methods of the ARMA family has the same concept as the methods studied in Moving Averages ...
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1answer
231 views

Detecting Outliers in Time Series (LS/AO/TC) using tsoutliers package in R. How to represent outliers in equation format?

Comments: Firstly I would like to say a big thank you to the author of the new tsoutliers package which implements Chen and Liu's time series outlier detection which was published in the Journal of ...
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30 views

Time Series Econometrics: Cointegration methods for series with mixed degree of integration

I am performing a time series analysis on dataset ranging from 1974-2008. I have performed Augmented Dickey Fuller tests and Phillips Perron tests to check the stationarity/ order of integration of my ...
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1answer
61 views

How do I detect state change in multivariate time series?

I have a multivariate time series . For each row in the data we have the values of inputs and a label for stability (0 or 1 ) . What are the algorithms that can detect the stability for an unlabelled ...
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26 views

Centering vs. Standarizing which one is better? [duplicate]

Two approaches have been proposed in order to overcome the issue of multicollinearity if we have interaction variables which are mean centering and standardizing (z scores). You can check No.2 in this ...
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40 views

How do I deal with asynchronous data in financial time series?

I have tick by tick data of two financial time series. I am trying to do online regression between the given two time series. But I am stuck due to asynchronic nature of given financial time series ...
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16 views

Correlation between sensors

Background: A home wired with multiple sensors, measuring attributes like temperature, light, motion etc. In addition, a multitude of actuators that can carry out an action like opening a door, ...
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128 views

How to compare time series with cyclical data, and describe any changes or trends

I have a bunch of time series where the data has a natural (known) cycle, for example daily or annual (or both). Here is an example (this is 6 years worth of temperature data sampled hourly): ...
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28 views

Analysis of proportions over time

My knowledge of statistics is limited and I am looking for resources to read on the matter if possible. Anyways, I am currently trying to estimate a confidence interval for a proportion over time. ...
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41 views

How to implement a metropolis hastings algorithm to find the posterior pdf of a time-dependent parameter?

Assume that I have a time series observations denoted by Yi where i is from 1-5000. yi=β1 x1i + β2 x2i + β3 x3i + Ci; Here x is the input. I have to find the values of Betas. But, I'm taking all ...
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46 views

How accurate is F test in panel data

I heard that the F-test is to advice you whether to use fixed effects or pooled OLS. However, I didn't find any details about it in books. Only in a very few studies. What is the hypothesis of the ...
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53 views

Is it ok to transform a logarithm variable to z score

I have a variable that has 57 kurtosis, so I decided to transform it to log. However, I have multicolleanirity problem due to interacting this variable and others with another variable so I am using z ...
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43 views

temperature prediction algorithm

I found an interesting problem in a contest on temperature prediction: https://www.hackerrank.com/contests/expansion-challenge/challenges/temperature-predictions It is not about forecasting the ...