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

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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!
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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 ...
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16 views

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

I have data sets in which 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 the last few ...
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1answer
13 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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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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19 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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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 ...
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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
138 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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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
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
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 ...
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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 ...
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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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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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3answers
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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2answers
126 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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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 ...
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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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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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14 views

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
37 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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1answer
16 views
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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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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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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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4 views

R script for Center Timing of Streamflow [closed]

Might someone have an r script for Center Timing (CT) of Streamflow for hydrologic analysis? Your help is greatly appreciated.
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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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1answer
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
453 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, ...
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27 views

Fitting a VARMAX model using MTS library in R

I am trying to fit a VARMAX (vector autoregressive moving-average with exogenous variables) model to some synthetically generated data using the MTS library available in R. I found that there is only ...
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17 views

Analysing the difference between time series

I have several sets of experimental results. Each set of results is composed of ten time series. Only one variable is changed between the sets of results. The changing of a variable $V$ makes the time ...
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Stationarity (ADF at intercept and NONE level, PP) and Granger casuality tests in Stata [closed]

I am doing research on FDI and Economic growth in Pakistan. I have 5 variables. I want help in interpretation of ADF and PP tests in Stata.
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1answer
41 views

Time series forecasting with R

I try to forecast my web visitors on the web site for 10 future days using time series. My time series is daily. I have used an auto.arima() model. Considering ...
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12 views

Training on time series data with a small number of examples

The data I have is collected from 16 smartphones - it's made up of discrete readings from various sensors (eg. accelerometer in 3 axes, intensity of sound in various frequencies etc.), at regular ...
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R: forecasting a binary time series using the VLMC package [closed]

I would like to ask some clarifications on the method: predict.vlmc My problem is to forecast a binary time series one period ahead. I have a time series bin2 of ...
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58 views

Walkthrough of building a time series model (on real examples)

I'm trying to find some real examples showing someone going through the full process of building a time series model (how they deal with trends and seasonalities, what features they picked, etc). Does ...