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

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Maximum Lag Length in Granger Causality Test for intraday ,1 minute, time series?

I have 2 time series having 1950 observations each. The time series represent intraday, 1 minute, close prices of stocks. Those 1950 observations cover period of 5 trading days, meaning that each ...
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19 views

prediction of variable in the future?

I have some data from sensors in my phone.I have their respective battery levels at each timestamp the sensor readings were recorded in phone.My aim is to be able to predict, lets say that i have ...
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67 views

Why are econometric analyses valid when the subject of study is inherently different?

I am reading numerous articles pertaining to unemployment as references for my own work. Yet I've encountered many where they use long time series in countries which have had some sort of pertinent ...
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39 views

Seeking basic advice re. contingency matrix for time-limited predictions

I am looking for advice on how to construct a contingency matrix ... A subject is measured on day 1 and a score is computed. This is repeated daily generating a series of scores. If on a given day ...
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30 views

Vector autoregression with interval lag terms in R?

I'd like to perform vector autoregression on a two variable system. I know that the signals $x$ and $y$ have a time lag of > 100 time points, and thus any fit with that many time lag parameters is ...
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75 views

Simple Time Series Analysis

Suppose we have collected a set of data points $\{a_{t}\}$ at time $t = 1, 2, ..., t', ..., n$. Each data point consists of the following attributes: ...
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28 views

Testing Contemporaneous Correlation

Suppose I have the following time series: ...
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31 views

How can I make sure that an LDA implementation works?

I am currently experimenting with neural nets for classification of on-line handwritten data (hence: not pixels, but time series data). To do so, I use several toolkits (internal development of my ...
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2answers
119 views

very high frequency time series analysis (seconds) and Forecasting (Python/R)

I have high frequency data (observations separated by seconds), which I'd like to analyse and eventually forecast short-term periods (1/5/10/15/60 min ahead) using ARIMA models. My whole data set is ...
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19 views

How to simulate a structural break time series? [migrated]

I want to know how to simulate the following structural break autoregressive time series: $\begin{cases} Y_t = 0.9Y_{t-1}+\epsilon_t & \text{for }1\le t< 50\\ Y_t = ...
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1answer
23 views

relationships between 3 variables

I have 3 data sets. one is the water level of a lake at 15min intervals, one is the water level of a pond next to the lake (also at 15min intervals) and one is the wind speed over both the lake and ...
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4 views

Using dates in R for Theil-Sen [migrated]

I am trying to use dates as my X variable in a Theil-Sen slope estimation and I am having difficulty using the R package zyp ...
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30 views

Identifiability in linear regression and time series

The multivariate linear regression model is given by $\mathbf{y} = \mathbf{X}\boldsymbol{\beta} + \boldsymbol{\epsilon}$, where $\boldsymbol{\epsilon} \sim \mathcal{N}(\mathbf{0, ...
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40 views

How to determine the correlation between data sets with the same period but different sample rates?

I am trying to determine the correlation between two sets of data points which span the same time period (20 minutes) but have different resolutions. The first set was recorded at 1-minute intervals, ...
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1answer
20 views

How to validate a lognormal random walk for time series data

I am currently working on a project where I need to simulate the prices of a set of $D$ substitutable commodities over time. I was hoping to do this using the following $D$-dimensional lognormal ...
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1answer
31 views

The likelihood that a time series is generated by certain ARMA(p,q) ?

I have a group ( only 20 of them, each one has 170 time pointers) of time series that I can consider as "GOOD", meaning, they have consistent statistical characteristics. I am not sure how they are ...
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9 views

Discovering dis-associations between periods of time-series

I'm interested in discovering some kind of dis-associations between the periods of a time series based on its data e.g. find some (unknown number of) periods where the data is not similar with the ...
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10 views

Are there free APIs for searching news articles that I can use to collect trend data in news coverage? [migrated]

I am working on a data-visualization web application that looks at trends in American news media coverage over time. It takes a keyword (or keywords), a date range, and a time increment as parameters ...
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1answer
34 views

How to analyze personal time series

I have a time series data of multiple subjects' performance over the time as well as time series metric of their mouse movement. In other words, for every subject, there are two graphs: Performance ...
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16 views

Factor analysis using “outliers-only” time series

Some background I run a factor analysis of a time series $Y$ using a standard OLS model with n+1 independent variables $(F,X_1...X_n)$, where $F$ is the main factor (from an explanatory power ...
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1answer
59 views

Cointegrated Vector ARMA (CVARMA) Model vs. Dynamic Factor Model (DFM)

Two questions regarding the equivalence (or lack thereof) of vector error correction model (VECM) cointegrated vector ARMA model (CVARMA) and dynamic factor model (DFM): Can every VECM CVARMA be ...
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2answers
179 views

Pattern recognition with time series analysis

I'm looking for some good pointers to pattern recognition with time series. Possibly something practical that can be easily understood. As a toy example, think about collecting data from an ...
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1answer
20 views

Discriminating for early detection of problems

I could (please) use some suggestions on how to tackle an issue that has been brought up where I work. When a new product is launched, our company tracks how many AND what type of replacement parts ...
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17 views

How does one adjust for data snooping when using ACF and PACF?

ACF and PACF are routinely used for approximate identification of a time series model, e.g. as described here. Say, one takes a look at the plots and guesses that it's something like ...
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31 views

How to interpret ACF and PACF plots

I just want to check that I am interpreting the ACF and PACF plots correctly: The data corresponds to the errors generated between the actual data points and the estimates generated using an ...
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1answer
21 views

If I am comparing actual data vs. forecasted data, is the Durbin-Watson statistic useful?

We are comparing our forecast vs actual data from the same time period and was using the mann-whitney test to help provide evidence our samples were not different. Someone challenged us saying the ...
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33 views

How to combine short term and long term time series?

I need to combine two traffic data series which are long term ( with 15 S / 30 S/1 minute interval) and short term( with 2 S/ 3 s) for my research purpose. These two types of data series reflect ...
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15 views

updating a forecasting model including the new observed data with the historical data

I want to have a one week ahead forecast for my data which includes a four years of daily historic data (three years are used as train set and the 4th year is used as the test set). I can use three ...
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1answer
15 views

Ensemble in stochastic process

I am learning a time series and forecasting course.In the book "The Analysis of Time Series by Chris Chatfield" it says that We only have single outcome of the process and a single observation on ...
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1answer
142 views

What if the trend is changed?

I want to forecast tourist arrivals using time series analysis. I expected to use monthly data from 2000-2013. But due to the civil war, the trend was changed after 2008 as in the following plot. ...
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14 views

NARX model to predict future values

I have this problem , where I have to predict a value of a indicator which depends on 270 other predictor variables. I read the time series modelling and prediction on MATLAB , which took the example ...
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1answer
25 views

My transfer function has non-stationary inputs, but a stationary output. Should I difference both the inputs and outputs during structure estimation?

I have a system of two inputs and one output that I'd like to model using the following Box-Jenkins transfer function ("dynamic regression") structure: $$y_t=\frac ...
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2answers
68 views

How to check if a series has been seasonally adjusted correctly?

I am a bit puzzled here and would like to understand how to check if a time series has been seasonally adjusted correctly using X-13 Arima. After seasonally adjusting time series using X13-ARIMA ...
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1answer
24 views

Very different Neural Network test errors for same architecture

So I'm doing a time series prediction, and assessing the capability of the ANN to predict that time series. I am using Matlab's neural network toolbox functions, and the training parameters are the ...
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70 views

are qqplots appropriate for time series?

I've seen that qqplots are a very useful tool to check model assumptions. In particular to analyze the residuals. However, it seems that is based on data ordering and therefore assumes a atationary ...
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11 views

How to compare the volatility of quarterly p&l of two firms in the same sector?

I want to compare the volatility of the historical quarterly profit and loss (p&l) data of two or more firms operating in the same sector and determine whether the volatility of p&l of these ...
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31 views

Is it reasonable to use a combination of two forecasting models for a dataset?

I used tbats to fit a model for a 3 years of historic data and the values work fine but as I did not include holidays, holiday predictions are really off. I used arima with regressor (holidays at ...
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54 views

Bartlett's Sphericity Test for PCA Failure

I am using XLStat for a PCA of time-series water chemistry data. I have 23 analytes and 29 samples. I am using a correlation matrix for PCA as I find it more interpretable in the context of ...
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42 views

Find the median individual with observations on multiple variables over time

I have a question regarding the use of median. We collected data concerning disease development on hosts. We gathered the evolution of three variables over time on individuals. Their characteristics: ...
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89 views

Obtaining the SarimaX equation from the arima coefficients

I have a SarimaX model with three regressor variables: ...
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18 views

Synchronize time series by date and time in R

e.g. i have two time series that describe how much money in specific currency i spent at specific date: ...
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49 views

Time series - plotting continuous and categorical variable

I have one dependent continuous variable and an independent categorical variable. Each one minute window on a time series is marked with one category, for example 10:00 - 4, 10:01 - 1, 10:02 - 5, ...
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multidimensional time series nonlinear parameter estimation

I am trying to fit time series data for performing parameter estimation of a nonlinear multidimensional dynamical model (grey-box). At the moment I'm successfully using MATLAB's ...
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22 views

What type of model should I use? (Time series, univariate, dependent variable is a count)

I have a univariate model in which I am looking to predict the number of articles per week in a newspaper about a protest (count data) by how many arrests of protesters occurred per week. I have 148 ...
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1answer
44 views

How can one say if a model is poor based on RMSE value

I have a general question about the value of using RMSE to see if a forecasting model is poor. I used the forecast package in R to find forecasting models for ...
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8 views

Use cases for P-Kernel for SVMs

I've been reading the book by Cristianini on Kernels (2004) where generative kernels (like p-kernel and fisher-kernel, not to be confused with polynomial kernel!) are described. I am interested in ...
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29 views

What statistical analyses should one perform on ensemble forecasts (given a measurement)?

I have an ensemble of time-series predicting a scalar variable. Additionally, I have a measurement time series of this scalar variable. Which statistical analyses could and/or should I perform to ...
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129 views

How to characterize abrupt change?

This question may be too basic. For a temporal trend of a data, I would like to find out the point where "abrupt" change happens. For example, in the first figure shown below, I would like to find out ...
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244 views

How to find the functional form of pdf from time series using Kernel density estimate

I will appreciate help in determining the functional form of the probability density function (pdf) for the following case. I have read about Kernel Density Estimate for the case when we don't have ...
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25 views

prediction for data including weekly and annually seasonality and dummy variables for holidays

I have a three years of daily data for number of orders a trucking company receives everyday. Number of orders are high during weekdays and they have a huge decrease for weekend. I used msts to ...