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

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Which model to predict air cleanness (air pollution) in daily-basis?

How hard it is to predict air pollution? My friend is an agronomist: he is doing some research on some small plants. The plants are very sensitive to air pollution in urban areas [need deep ...
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6 views

Forecast error for AR and MA process

AR(p) process is denoted by: $X_t=\mu+\alpha_1(X_{t-1}-\mu)+\alpha_2(X_{t-2}-\mu)+...\alpha_p(X_{t-p}-\mu)$ I don't understand forecast error. Let $\epsilon_{t+l}$ be the forecast error t $l$ step ...
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1answer
16 views

SARIMA model equation

Can someone please tell me in the book here how is this SARIMA equation obtained? I know that AR(1)=$Y_t=\alpha_1Y_{t-1}+e_t$ Non Seasonal AR(1)=> $Y_t(1-\alpha_1B)=e_t$. My question is what ...
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20 views

Time Series Stationarity

I am confused of why my Dickey-Fuller test is significant (which implies stationarity), while the time series clearly exhibits a deterministic trend?
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1answer
11 views

How to test a time series' serial correlation with ties in R?

I was trying to test serial correlation for a time series measurements (x1,x2,...xn). The problem is that some of them happens in the same date, the time points are ...
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1answer
296 views

Time-varying Coefficients

I have time series data on fish catches from 1950-2011. I wish to implement a regression model with varying coefficients. I'm aware that cox models etc. exist and implementation via the ...
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1answer
214 views

Multiple values in a timestamp

I am working with a time series (discrete) that has ideally 1 value per time stamp. In some cases, we are seeing multiples that have a wide range all recorded with the same time stamp. Up to now, we ...
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6 views

Generalized additive mixed model in R - specifying a fit function

The data in question comprise two response groups (no response vs. stress marker), different individuals, repeated measures ...
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2answers
170 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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3answers
95 views

Are time series methods only good for forecasting?

Many time series methods are oriented solely in terms of forecasting (e.g., ARIMA). However, it seems like a growth curve modeling framework (i.e., random coefficient modeling) can do virtually ...
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1answer
66 views

How to normalize time series?

This is a general question on normalization of data so that all the variables are within the same range. Why do we normalize data in pattern classification? How to normalize time series which is ...
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1answer
191 views

Forecasting model inputs that are both auto-correlated and are calibrated over time?

How does one account for model inputs that are both a) auto-correlated and b) calibrated over time? I'm interested in forecasting the outcomes of sporting events. Let's say that each team has a score ...
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1answer
19 views

Best practice for ADF/KPSS unit root testing sequence?

I've been quite confused by the various unit root testing strategies recommended in the literature, so I was hoping others may have some advice on the best way to proceed using ADF and KPSS tests. ...
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16 views

How to estimate the percent of the variation of a time series explained by another time series (non-stationary)?

I've been learning about time series analysis because I want to understand how much groundwater level changes in an aquifer affect land subsidence (land sinking). I have two time series: (1) ...
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16 views

How to detect the time dimension in a candidate time series?

I am trying to build a quantitative method for detecting that a multivariate dataset is in effect a time series, and for estimating its parameters. The Runs Test would be used for quantifying the ...
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1answer
105 views

How to test for Pearson correlation when one variable is fixed on date?

I have 4 groups of different respondents, each group surveyed on four different dates (points of time). All respondents have answered a psychological questionnaire related to their perception of death ...
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1answer
321 views

How to fit a simple count time series INAR(1) model

I am trying to perform a simple time series analysis with count time series data. My data is a sequence of small integer values like 0,1,2 and 3. I learned from various sources that INAR model would ...
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1answer
228 views

Determining the best correlated time series

Before asking, I read similar questions, but none of them lead to satisfying answers for my specific interest. I want to homogenize a climate time series of precipitation of the Dominican Republic ...
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12 views

Clusters as input for classification

I'm currently performing clustering as a batch job and then in real time I'm assigning new points to cluster whose centroid is closest to new arrived point. The other approach that I see is to ...
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27 views

Guidelines to estimate using MLE from this definition of error function

Consider a stable causal, single-input/single output, linear time-invariant, discrete-time system. The noisy output is $y[n] = \sum_{i=0}^{p-1} c_i d[n-i] + w[n]$ where $c_i$ is the real-valued ...
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1answer
49 views

Hourly predictions using time series

I'd like to build a model based on time series. I have a dataset with records every 30 minutes for three months. What is the difference between modeling these data with the following kinds of ...
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5answers
772 views

Estimating same model over multiple time series

I have a novice background in time series (some ARIMA estimation/forecasting) and am facing a problem I don't fully understand. Any help would be greatly appreciated. I am analyzing multiple time ...
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3answers
148 views

Is there any tool that can do Vector ARIMA modeling in time series

Vector ARIMA model is used in multiple time series analysis. I am just wondering if there is any software or tool can be used to build the model. Some tools,like R, can only be used to predict the ...
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2answers
80 views

Longitudinal k-means sample data

Having finished the Coursera's Machine Learning course, I would like to put the theories into practice. Thanks in advance on guiding a newbie! In particular, I am looking forward to some guidance ...
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15 views

cumulative uncertainty with time series predictive model

So I have a time-series with a set of variables a, b, c... and another measured variable y. What I do is using the initial state of a,b,c and y (at t0), I predict what y "should" be at the next time ...
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3answers
340 views

Filtering techniques and noise

Suppose we have some house price data for 30 years (1970-1999). This is yearly data (30 data points). Suppose some major event $X$ happened on 1980. I want to see whether this event affected prices ...
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23 views

Why does NSDIFFS (R forecast package) never show seasonality? [migrated]

I've been using the EViews statconn DCOM interface to loop a large number of series from FRED through the nsdiffs(test=c("ch")) function in the forecast package of R to examine what percent of them ...
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4answers
935 views

Random generation of ARMA(2,2) Gaussian time series

I get very poor replication of longitudinal parameters from my own program using the Box-Jenkins model. I had no such problem with my own program generating AR(1) Gaussian data. Is there some trick ...
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19 views

How can we compute cumulative change rates for time series data? [on hold]

Take the annual precipitation data for some area from 1960 to 2008 as an example. How can we compute cumulative change rates for such data?
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11 views

Applicability of Hilbert-Huang Transform for linear trend analysis

I have a question about the applicability of the Hilbert-Huang Transform / empirical mode decomposition (HHT/EMD). Suppose I have a time series dataset in which there is probably an N-year periodic ...
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2answers
198 views

How to extract long run and short run coefficients from ARDL (UECM) estimates?

I have estimated ARDL(UECM) in eviews but I dont know how to specify or extract the long run an short run estimates/coefficienst? what is the standard procedure to do so?
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1answer
425 views

R package TSA: how to interpret the IO coefficients output of the arimax function

I was playing with the TSA package in R and wanted to test the arimax function to the solution provided in Pankratz's Forecasting with Dynamic Regression Models, ...
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1answer
129 views

Nearly constant time series

I want to analyse temporal interactions of some time series by means of the Box-Jenkins approach to find out which time series are predictors of another one (with the help of prewhitening and ...
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15 views

Time series model of prevalence

I have a collection of samples from which I have estimated prevalence on an annual basis using a logistic regression model. The response variable is whether or not the focal species was present in ...
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1answer
114 views

Issue in graph construction

I have a symbolic representation of time series obtained from SAX toolbox. I was wondering if it is possible to construct a graph where each node represents a unique symbol and the edges represent the ...
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2answers
155 views

Regression analysis for more than one categorical variable in time series

I have a time series data for shipment with following variables: Year: 2008, 2009, 2010, 2011, 2012, 2013 Month: jan, feb, ..., dec Number of ordering days Shipment Volume I want to know the ...
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24 views

Dynamic Time Wrapping for finding divergence in timeseries data

I have the time series information of various S&P500 sectors. I need to find which sectors are outliers and diverging from the bunch of sectors. As you can see in image below, in month of October, ...
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19 views

Selecting the best (or more suitable to the user/client) output from a set of forecasts

I have approximately 3000 products for which I have to forecast in every, say, 2 months. I have the code in place for different forecasting models such as ARIMA, forced seasonal ARIMA, STLF etc. Now ...
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1answer
135 views

R GMM - Error in solve.default(x$v, gb) : system is computationally singular: reciprocal condition number

I'm having the following problem estimating something in GMM in R. I have created a "Hello World" below. In principle, I would not need GMM to estimate the parameters, but I want to use it to obtain ...
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16 views

Comparing 2 time series in R

I was wondering what kind of tests one would use to compare these two time series. The first data set(in percentages) are results from a weekly survey that asks a YES/NO question on whether someone ...
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26 views

Can you generate confidence intervals for time series ETS forecast components?

Suppose you fit a time series with the ets function from the forecast package in R: ...
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2answers
101 views

Dynamic Time Warping for irregular time series

I have been reading a lot about Dynamic Time Warping (DTW) lately. I am very surprised that there is no literature at all on the application of DTW to irregular time series, or at least I could not ...
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12 views

Log returns and ARMA-GARCH models

I try to model currency rates volatility using GARCH models through the RUGARCH package in R. Starting from the observed currency rate series, I compute the log-return through: ...
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66 views

How to calculate probabilities based on cumulative of time series?

I am trying to do predictions on plant growth based on cumulative of time series data. Unfortunately I am not a statistician, just a programmer tasked with writing the application that does this (PHP ...
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15 views

Bootstrapping - Variance of Time Series with Micro-level Data

I have micro-level (individuals) time series data and I am able to calculate some aggregate statistic for each time period. The data is not a panel, so each month is a different cross-section of ...
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616 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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1answer
256 views

ZScore threshold and low values time-series

Example of z-score computation: 1 - E.g. Time-series: [0, 0, 0, 0, 1] Current: 1 Mean: 0.2 Std: 0.44721 Z = (1 - 0.2) / 0.44721 ~= 1.7888 2 - E.g. ...
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27 views

State space model with regression effects

I'm trying to show the following (exercise 3.11.4 from Durbin and Koopman (2012)): Show that the state space model defined by $$ y_t=X_t\beta+Z_t\alpha_t+\epsilon_t\\ ...
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110 views

How to test the ARIMA coefficients?

Which test is required to test whether coefficients estimated as part of ARIMA procedure is different from 0? And how does one compute this test? I am reading some procedures regarding the inversion ...
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1answer
334 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 ...