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

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429 views

Statistical comparison of two signals

I need to develop an algorithm that will compare two signals and generate some metric(s) to describe changes between them. Signal processing and analysis isn’t my strong point so I would appreciate ...
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1answer
25 views

How should I test for autocorrelation in this time series context?

I have data sets in which different people estimate a certain quantity. They potentially can see the estimates of anyone who participated before them, but in practice they're only likely to look at ...
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6 views

Question about number of observation in Generalized ESD

According to http://www.itl.nist.gov/div898/handbook/eda/section3/eda35h3.htm The number of observation is denoted by $n-1$ Why dont we just use $n$ instead of $n-1$? Is there any special meaning ...
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5 views

Use SAS to seasonally adjust month-to-month growth with underlying weekly seasonality

I've seen using R to seasonally adjust month-to-month growth with underlying weekly seasonality. Is there any program in SAS to do the same thing? I don't have SAS Forecast Server. Thanks!
4
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1answer
1k views

Lag length selection Granger causality test

Consider G-Causality on two stationary time series vectors (call these variables $X$ and $Y$), each with 100+ observations. It's daily financial market time series data. I have reason to believe that ...
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3answers
2k views

Unit root tests: how to decide if to include a trend and/or a constant

Applying a test to univariate time series data for checking if the series has a unit root or not, one is faced with a decision if one would like to test if the series is stationary around a constant ...
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0answers
5 views

Do I have endogeneity problem if I use year-over-year change data in AR(1) model?

My dependent variable is y(t)=data(t)/data(t-4)-1 with quarterly data and the model is standard AR(1) : y(t)=a*1y(t-1)+ b*x(t)+e(t). I 1was told that due to overlapping I should have endogeneity ...
5
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1answer
132 views

Regression slope that increases persistently as my sample size increases

I found a peculiar feature in some data that I am analyzing and was wondering whether there was a technical term for this type of phenomenon and whether anyone has come across it before. I am doing a ...
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1answer
14 views

Quasi-experimental design : time series analysis

I am busy designing a medical research for my masters(epidemiology)on time series analysis, comparing the trends of Pulmonary TB bacteriologically confirmed cases before and after the introduction a ...
3
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1answer
39 views

How to interpret and do forecasting using tsoutliers package and auto.arima

I have got monthly data from 1993 to 2015 and would like to do forecasting on these data. I used tsoutliers package to detect the outliers, but I do not know how do I continue to forecast with my set ...
2
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1answer
213 views

Increasing the accuracy of tbats() forecasts by factoring for correlations between different time-series?

This question builds on my previous question Forecasting Hourly Time Series based on previous weeks and same period in previous year/s. My project is to forecast the number of ~400 different types of ...
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10 views

Constant-output Markov chain in time-series prediction

Suppose a Markov chain with two discrete states $A$ and $B$. The probability of moving from $A$ to $B$ is $0.1$ and the probability of moving from $A$ to $A$ is $0.9$. Similarly, $B$ to $B$ has ...
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27 views

How are Markov chains used for time-series forecasting?

How are Markov chains used for time-series forecasting? Since the next state depends only on the current state, I would guess that I should first find the steady-state probabilities. To predict a ...
1
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2answers
208 views

Forecasting the target variable vs building a causal model and forecasting causal variables

I want to know the approaches people use to forecast lets say unemployment rate .... By itself it might not fit a time series model (ARMA) very well as the trend is dependent on many external factors. ...
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0answers
20 views

Change detection in hidden markov models

I have many questions about hidden Markov models. Let $Z_1$, $Z_2$, ..., $Z_n$ be the latent variables, and $X_1$, $X_2$, ... $X_n$ be the observed ones. Let's assume that the parameters of the ...
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0answers
4 views

Time-series variable normalization before using state-space models

I try to estimate a time-series with an SSM that I built. The problem is that model fit is not very good and I think normalizing variables might help. Both my dependent of some of my independent ...
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2answers
33 views

segmentation of univariate irregular time series

this is my first post. I have an irregular time series that exhibits large shifts in both mean and in the direction of the trend. It looks something like this (though this is far cleaner than ...
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1answer
118 views

How to determine “trendiness” of a time series

I'd like to be able to compare two timeseries as to their level of "trendiness" to determine which trends better. For example, assume two stocks, Google and IBM. Would like to understand approaches to ...
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9answers
3k views

Time series for count data, with counts < 20

I recently started working for a tuberculosis clinic. We meet periodically to discuss the number of TB cases we're currently treating, the number of tests administered, etc. I'd like to start ...
2
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2answers
179 views

Determining odd time series

I have a number of time series which are derived of same underlying data. However, the data in each comes from a different source, so they may be slightly lagged or differently enriched but ...
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2answers
95 views

What is the best model for time series data with independent and dependent variables

I have two different variables across a time series over a couple thousand time steps. I want to predict the values of the dependent variable (y) based values of the independent variable (x) in the ...
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0answers
16 views

How to estimate Vector Error Correction Model in a linear equation

I am confused about the Vector Error Correction Model (VECM). The main objective of my study was to determine the effects of public expenditure components on economic growth over 35 years. GDP is the ...
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2answers
139 views

Why is this time-series stationary?

I am using python for time-series analysis of count data and came across a problem where I have a time-series that to me looks non-stationary but the Augmented Dickey-Fuller test (implemented in ...
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0answers
20 views

Fit dispersal and migration movement in R using nls.Find AIC and Akaike weight for migration and dispersal using R [on hold]

I am trying to fit dispersal and migration movement in r using formula by Bunnefeld et al (A model driven approach to quantify migration patterns, individual, regional and yearly differences) but ...
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5 views

Coefficients for regression in levels from Estimated First Difference Coefficients

I would like to know if there a simple way to compute coefficients for a regression in levels after having estimated a regression in first differences. Having estimated yt - yt-1 = a + b(xt-xt-1) ...
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20 views

Specifying integration level of time series

How to specify the level of integration of $X_t$ in such case? I am familiar with testing integration in R, cointegration strategies, but which method to use in such case? In brackets there are ...
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1answer
19 views

Two-step Engle and Granger's procedure

If I want to check if there is cointegration between $X_t$ and $Y_t$ in the following model, is it enough to check p-value of Breusch-Godfrey test? The maintained hypothesis in this test is no ...
2
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1answer
112 views

Comparing data that has been recorded on two devices

I have two data loggers which are recording a physiological signal. Device A is a system that has been in place for many years, and records data ~once/minute. Device B is a prototype device which ...
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3answers
1k 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 ...
0
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1answer
211 views

Generating IMA(1,1) series

I'd like to generate a series that follows an IMA(1,1) process, where $θ$ is the moving average parameter. I generated the series based on different representations and I got different results, I'm ...
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0answers
9 views

Autocovariance Estimation and Stationary Processes

I am going to work on a project involving time series and therefore I am trying to understand some basic definitions. I am currently trying to grasp the autocovariance estimation procedure. When we ...
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1answer
45 views

How can correlation be 0 in % terms but 0.5 when measured in dollars?

I am trying to see if there is a causal relationship between Marketing Spend and Revenue on a monthly basis for the Jan to July 2015 period. I calculated the percentage change in Spend and the % ...
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26 views

Need time series visualization software with zoom [on hold]

I am responsible for providing time series data to my co-workers monthly as line charts. The plots consist of two series: the actual data and a moving-average smoothed line. I am currently doing this ...
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2answers
32 views

Cointegration Approach

I want to perform a cointegration test between metal prices in USA and India. For USA prices are in dollars per pound and for India they are is in rupees per quintal (100 kilogram). Before checking ...
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34 views
+50

How to train radial basis function for function approximation?

There is an Autoregressive model of order 1 (AR(1)) that is excited by a non-linear signal as the input: $$x_t = \rho x_{t-1} + u_t \tag{1}$$ The time series $u_t$ is generated from a Mackey-Glass ...
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0answers
14 views

Anomaly Detection: Pattern Recognition inTime Series

I am trying to implement an anomaly detection tool based on Pattern Recognition. The data I am working on are periodic.I extract the pattern from a training set and then compare it to data in the ...
2
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2answers
128 views

analyse peak distribution in time series

Sorry if my question is too simple, I don't have much of a background in statistics. So I'll just try to describe the problem I need to solve in practice. I'd like at least to find out what known ...
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0answers
39 views

Timeseries data analysis in R

I have a question about site, season and year differences in water quality, fish diversity and composition. To answer these I have collected fish abundance data as well as water chemistry data from ...
4
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1answer
96 views

What type of analysis to choose for this data?

I am trying to create a model of refrigeration having the energy consumption and the temperature over time. So far, I've tried regression but fitting this data into linear model seems impossible. ...
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3answers
417 views

Regression of data that includes a date

I have a dataset that contains a few hundred transactions from a three suppliers operating in 100+ countries over a three year period. We've found that the country of sales is not a significant ...
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10 views

Two - Step Engle and Granger ECM model for multiple variables in R [on hold]

I'm looking for a R package which will allow me to estimate the Two - Step Engle and Granger ECM model with numerous variables. I have looked at the apt package ...
1
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1answer
143 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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1answer
205 views

Time series modeling of choppy data

I'm trying to model 10 years of monthly time series data that is very choppy, and overall it has an upward trend. At first glance it looks like a strong seasonal series, however the test results ...
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2answers
3k views

Invertibility of AR(p) model

Notation: $\dot{Z}_t = Z_t - E(Z_t)$, so that it is centered at 0. $a_t$ stands for the residual and we assume the $a_t$ are independent and normally distributed with mean 0 and constant standard ...
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1answer
169 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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1answer
299 views

How to map a trajectory to a vector?

I have a series of data points in this form (timestamp, lat, long) for a set of users. Each user has a trajectory when he travels from point A to point B. There might be any number of points from A to ...
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2answers
43 views

R: Augmented Dickey Fuller (ADF) test

I'm having a problem with the Dickey-Fuller p-values and test statistic for unit root test in R. I tried using functions: ...
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0answers
9 views

Sum of covariances equals variance of sum OR: how to estimate the relative importance of a time series for a sum of time series?

I have n time series x1, ..., xn and the sum of these time series xsum = x1 + ... + xn. I observed that the sum of all covariances between each time series and their sum equals the variance of that ...
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2answers
245 views

R seasonal time series

I use the decompose function in R and come up with the 3 components of my monthly time series (trend, seasonal and random). If I ...
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1answer
223 views

Data analysis: Time series for Bacterial population data

Could anyone please help with data analysis. Briefly, I am studying how the population of a bacteria changes at different points (port 1 to port 10) within a biofilter over the course of 30 days(like ...