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

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How to work with index numbers?

I have Index numbers of Infrastructure industry. The base year for the first ten years i.e is 1993-94 = 100 and for the next ten years is 2004-05 = 100 My question is - How to work with index numbers ...
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Visualising complex data with various groups + sub-groups over time period

I have a data set that looks like the following: ...
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14 views

What is a good way to test a simple Recurrent Neural Network

I have coded up a simple real-value regression RNN in theano. What kind of dataset should I test it on? How should I go about testing it? My structure is: Univariate (for now) timeseries, ...
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1answer
15 views

Matlab's sizing of exogenous inputs to vector time series

Matlabs commands for analyzing vector time series (e.g., vgxvarx, vgxproc) accept exogenous inputs. I understand the explanation that each of p inputs can have q paths with r observations, requiring ...
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41 views

Independent variable has a known non-causal relationship with the dependent variable; is it still okay to regress?

To further elaborate on my question, assume that I have a time series dataset of Tax X and Tax Y, where in Tax X is paid by 100% of the sample while Tax Y is paid by 75%. Both taxes differ with ...
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37 views

Time series Analysis using LS

I know this is a bit of a broad question but generally if I have a time series and I want to measure whether it has trend according to time I do the following: I regress the series against time, ...
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109 views

Is 10 years data enough for forecasting?

I want to forecast demand for the cement industry. I have data for 10 years- Monthly data. Is that desirable for forecasting?
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Monthly indicator variables, decreasing in weight

I have a logistic regression with a response variable that is a proportion and predictors that are dummy variables for the month of the year, along with a few key exogenous variables. My ...
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39 views

Clustering by fitting many linear SVMs and clustering their weight vectors?

Let’s say I have a bunch of discrete sequence data, with each sequence belonging to some individual (there are ~1000 individuals and many more sequences). With a great deal of success, one can train a ...
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All of the series used in a model must be stationary at the same order of differencing

While practicing VAR analysis, all of the series used in the model must be stationary at the same order of differencing. Is this correct? For example, let $X$~$I(1)$ and $Y$~$I(2)$. Can I use these ...
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19 views

Factoring Fourth degree polynomial for invertible ARMA process

I have to represent a $MA(4)$ process as an $AR(\infty)$. In this regard, I need to factorize the polynomial $(1-\theta_1L-\theta_2L^2-\theta_3L^3-\theta_4L^4)$ to have a representation $(1-z)^{-1}$. ...
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Filtering to avoid the Slutsky-Yule effect in a moving window average?

Can anyone suggest a generally accepted method of filtering time series data to avoid the appearance of artifactual oscillations when smoothing the data using a moving window average? Is it simply a ...
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12 views

Does VECM use the stationary series or the originals ones?

I have some cointegrated series and I decided to build a VECM model. (I differentiated them twice in order to get stationary series and that led me to believe that they might be cointegrated - I ...
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21 views

Johansen cointegration test: interpretation of results in EViews

I am not sure whether I am interpreting the cointegration test correctly. This is the test result: Because of the probability of the test I understand that my series are cointegrated of order 2. ...
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18 views

How to calculate Accuracy for regression and time series models?

What is the best way to find accuracy for regression? What is the best way to find accuracy for time series models?
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83 views

ARIMA model fits what kind of data

What kind of data fits ARIMA model well? If not ARIMA, what are the other good models that can be used to forecast the time series data?
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21 views

How to transform this time series data?

enter image description here Given in these plots above is the US unemply. data since 1948 till recently a month back. I tried using a log and difference transform to make the data look more ...
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1answer
22 views

Ensemble time series prediction from two separate models

I have two different forecasts that are produced by ARMA models using two different data samples. The difference between the two data sets is their size: one used data from 2013-2014 and another used ...
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2answers
68 views

Why ever use Durbin-Watson instead of testing autocorrelation?

The Durbin-Watson test tests the autocorrelation of residuals at lag 1. But so does testing the autocorrelation at lag 1 directly. Plus, you can test the autocorrelation at lag 2,3,4 and there are ...
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Trend analysis for change in multivariate distribution over time

At each time point, I have a multivariate distribution $x=[x_1,x_2,x_3]$. I don't have that many time points around 3-15. I would like to know whether the change of the distribution over the time is ...
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23 views

How to compare two data sets sampled at different time?

I have two time series $X$ and $Y$. These two time series contain features, $x_i \in R^{n \times 1}, i = 1...n_x$ and $y_j \in R^{n \times 1}, j=1,...,n_y$ sampled from two subjects($x_i$ are ...
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Large differences in ARFIMA parameter $d$ using different estimators

I am trying to estimate parameter $d$ for ARFIMA model using different methods: Hurst, ML, fdSperio, fdGPH and the function arfima which selects the best fit ...
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5 views

R predict on xts object not generating dates for future forecasted points [migrated]

I have a data frame where one column represents my daily observed values and a date column formatted "2014-10-01" using the as.Dates function. I'm creating an xts object doing the following: ...
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Where is the dominated convergence theorem being used?

I am trying to fully understand the proof of a theorem, I only have a problem with the application of the dominated convergence theorem. For the sake of completeness I will upload the whole statement ...
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38 views

How to measure the goodness of fit of a GARCH model?

When we talk about the linear regression, we have $R^2$ to measure the goodness of fit of the linear model. Here is the problem, do we have a similar statistical measure to assess the goodness of ...
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17 views

Finding optimal lag order for an exogenous regressor in a VAR model

I can't use VARselect as it gives lags in a VAR model which considers all the variables to be endogenous. In my case, one of the variables is exogenous and affects dependent variable with a certain ...
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5 views

How to load new data into ntstool in matlab? [on hold]

I am using neural network for time series prediction using ntstool in matlab. But in the tool ,there is an option to load data set from the examples. How to load my data set into the tool? Please help ...
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29 views

Negative cointegration

I am new to the topic of cointegration and my question might be trivial. Let's say $X_t$ is an increasing series and $Y_t$ is a decreasing series; is it possible that they will be cointegrated?
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58 views

Most accepted theory to analyse trend in data series

I have pollutant concentration for long period I want to determine trend. I have read some of the question answers in this blog regarding same . I have few queries. What is most accepted theory to ...
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How to identify functional form of relationship between response & input series in dynamic regression/arimax?

Problem statement A US insurance company advertises on national television in an attempt to increase the number of insurance quotations provided (and consequently the number of new policies). ...
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27 views

How come Exponential Smoothing without trend producing astonishing results when there is trend in the time series

I have a time series and a plot of it is presented below for consideration. A linear trend was identified in the series both visually and using statistical tests such as Cox-Stuart and ManKendall. ...
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63 views
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Determining the effect of number of likes

Let's say I have marketing data and I need to determine how effective the marketing is. The marketing strategy is to publish facebook posts at inconsistent intervals. The goal is to see how the ...
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53 views

Property of the autocovariance function in time series

In the framework of time series analysis Why does $\lim_{n \rightarrow \infty} n^{-1} \sum_{|h| <n} |\gamma(h)| = \lim_{n \rightarrow \infty} 2|\gamma(n)| $? The LHS (left hand side) sequence of ...
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A continuous function of a sequence of random vectors converges in probability to the function of the limit

Proposition: If $\{ X_n \}$ is a sequence of k-dimensional random vectors s.t. $X_n \overset{p}{\to} X$ and if $g: R^k \rightarrow R^m$ is a continuous mapping, then $g(X_n) \overset{p}{\to} g(X)$. ...
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Fitting a CGARCH-M model

I'm dealing with a CGARCH-M model that the long and short-run volatility components have different effects on returns. Here are its mean and variance equations: Mean equation: $$ y_t = \alpha + ...
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31 views

Principal Component Analysis on Time series data and panel data

I am trying to build an index on infrastructure and compare the index over the years and between nations. Since the variables are highly correlated with each other, review has suggested me to proceed ...
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23 views

what is the size of data should be predicted to make the predictive model valid

if I have time series with 1000 values , and I want to build a predictive model , how far in the future should i successfully forecast to make my predictive model valid, is there any condition or rule ...
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38 views

Correlogram and ACF/PACF applied to US index of unemployment rate

This eviews workfile contains US index of unemployment from 1960 to 2008 quarterly. I'm trying to understand ACF and PACF. Below is a correlogram for the first 24 lags: What can the correlogram ...
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87 views

Making sense of the first difference regression model

There must be a fundamental error in my approach. Let's start by stating we have a simple regression with two variables $X_t$ and $Y_t$: $Y_t = BX_t + e_t$ Where $B$ is the coefficient and $e_t$ is ...
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38 views

Interpreting the result of decomposing time series

I don't have a lot of experience working with time series data. Now I have a 3 year, monthly data for several entities (you can think about them as different stores), that I would like to do some ...
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28 views

Is series cointegrated if residual is stationary under time-varying coefficient regression?

Traditionally, if $x_t$ and $y_t$ are both $I(1)$, they are cointegrated when there exists some linear combination $z_t=y_t-$$\gamma$ $x_t$ such that $z_t$ is stationary or $I(0)$. My question is if ...
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34 views

How to use SVM to do time series prediction?

I want to know how to use SVM to do time series prediction? what the differences of input vecvtor X of our model between time-series prediction and standard kernelized regression problem?
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38 views

What is the meaning characterizing a model as “conditional mean”

I've been going through time series material of late, trying to re-invent myself as a practitioner in the field. Until I got to the point of actually trying to Matlab some models, I had never run ...
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35 views

Best way to account for time lags in logistic regression (GLM or GLMM)

I am trying to determine the best, most conservative way to account of time lags in a logistic regression type analysis (a generalized linear model with or without mixed effects). I am working with ...
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14 views

Difference between autocovariance and autocorrelation [closed]

I read from a book when i read about Yule-Walker estimation that "autocorrelation has nicer properties than autocovariance".. can any one tell me why please
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Need an effective way to show distribution changes over time and outlier reoccurence

Does anyone have suggestions on the best way to approach this problem? I have a large dataset (over 200k+ per day) in a MySQL database, that consists of a single record per user per day with a ...
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Finding the optimal combination of independent variables for a constrained dependent variable

I'm currently working on power plant time series data and my main objective is finding out the optimal combination of independent variables which would keep "SO2 concentration (dependent variable) ...
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19 views

Seasonal component in irregular time series

Is it possible to identify seasonality in a Time Series that is irregular? I am currently working with a time series that is being periodically constructed (via crawling), but these crawled ...
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How can I find Matching between a data set with given data set groups

I have a variability data new one, I would like to find the matching between given data set with group of data sets, which one among the data sets group has matched with the new data set. eg: A, B, ...
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How do I obtain the “Anomaly series” of a time series?

I have a time series of the Sea Surface Temperature (SST) of the Caribean Sea and I have to obtain the anomalies of that time series. ...