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

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Dickey-Fuller and $\phi_i$ Joint Hypothesis'

I am reading Applied Econometric Time Series by Enders, where he talks about a Dickey-Fuller test example (pg 209). As it is known D-F have different tests for trend, drift, or regular random walk ...
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9 views

Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
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8 views

How to check stability condition of VEC estimates in R?

I am estimating a VEC model and need to check the stability of its parameters. The vars package has a function to do this on an object of class varest generated by ...
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6 views

Association analysis of different angiogenic markers with different time points

I would like to know the statistical tests which can be used to measure the association of the angiogenic measurements, measured at five different time points, with a biomarker. Please provide your ...
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12 views

Is there a classification model with possibility to set transition probabilities for each sample?

There are models where we can to set initial transition probabilities between classes like Markov models. But what if we need to change the probabilities dynamically depends on all previous ...
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5 views

Review of methods for handling missing and/or unevenly spaced data in time series

This question concerns the general problem of working with data that might have missing and/or unevenly spaced values. Let's call this "real" data. Specifically I am calculating rolling variance and ...
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6 views

General to specific approach vs information criterion

In ARDL model I want to determine proper lags for model. I have two option for this. The first is General to specific approach and deleting all insignificant variables. And the second is using ...
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7 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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14 views

Seasonal adjustment for daily/weekly data [on hold]

I have daily sales data which display strong weekly seasonality as well as monthly seasonality. It means that there are spikes/dips at the end of each week and greater spikes at the end of each month. ...
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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 ...
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35 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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23 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 ...
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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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24 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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31 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 ...
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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
143 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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17 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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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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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

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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1answer
20 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 ...
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42 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 ...
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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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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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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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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 ...
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130 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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11 views

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

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 ...
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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 ...
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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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46 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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In which languages can I estimate a VMA model?

In which languages/environments are there tools to estimate a VMA model of a given order? That is, given $q\in\mathbb{N}$ and a multivariate time series $y_t\in\mathbb{R}^d$, $t=1,\dots,T$, a function ...
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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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17 views

Programming Hausman Endogeneity Test [closed]

I want to program a hausman test in R, which can handle dynlm's, models without constant and incorporate optional HAC standard errors. For now i have the following code (x_en = suspected endogenous ...
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10 views

Rolling Regression with 2SLS using rollapply() in R

i want to do a rolling regression with 2SLS: First, i wrote a function for 2SLS with only one argument: the data-matrix (dat2 contains first differences of real aggregate consumption expenditures, ...
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22 views

Statistic to measure grouping (or intensity) of observations

I'm looking for a statistical technique that can measure the level of grouping or intensity of observations. I'm not sure what the proper terminology is, so I will try to explain my question through ...
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1answer
38 views

Identifying intervals in a time series

I know, I know, this must have been covered many times before, but my belief is that I don't need the usual robust solution... Here is a time series: I would like to automatically detect the ...
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9 views

Looking for an old study showing problems in trend analysis

I remember taking a paper which showed a major city would be under horse manure and garbage if the current trend continued.Of corse cars came to be and the trend did not maintain itself. Does anyone ...
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40 views

Should I ignore negative prediction values?

I have the following time series of count data: ...
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27 views

How can I predict one time series using another time series?

Necessary Information: I have time series $X_t$ and $Y_t$ and $Z_t$, $t=0,...,N$. I want to develop a model to use $X_t$ to predict $Y_t$ where I know there exists a relationship $Y_t = Y_{t-1} + Z_t ...
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15 views

Standard deviation in cumulative displacements reconstructed from noisy velocities

By solving an overdetermined problem one gets velocities at different time intervals with known standard deviations. The cumulative displacement is then reconstructed from computed velocities as ...
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30 views

Fitted values from regression on first differences

I wish to predict variable $y$, and so I am tempted to estimate $$ y_t = \beta_0 + \beta_1 x_t+ u_t $$ Looking at a plot of $y$, the series does not seem stationary. Instead I regress like so: $$ ...
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135 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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2answers
33 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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12 views

causal impact R package- finding individual day values

In the causal impact R package is there a way to get the counterfactual values and confidence intervals for each day rather than average or cumulative?
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33 views

Calculate probability of event from ecdf in R

I'm using R and would like to calculate the probability of an event happening. I used the ecdf function on daily revenue (month-to-date). I have a target and a daily number necessary to hit target ...
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2answers
454 views

What does this notation mean?

Could anybody tell me what is this model? What does it mean? $$\Delta Y = C + a(Y_{t-1} + bX_{t-1}) + c\Delta Y_{t-1} + d\Delta X_{t-1} + \varepsilon_t$$ Where $\Delta$ is the differencing operator, ...