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

learn more… | top users | synonyms

1
vote
0answers
44 views

Constructing 95% confidence intervals of coefficients in ARIMA model

For the recurrence relation below I simulated it in R with arima.sim and used arima.sim(data, order=c(2,0,2)) to estimate the coefficients. $x_t = x_{t-1} - \frac 13 x_{t-2} + w_t + \frac 14 ...
0
votes
0answers
18 views

Why the correlatio=corARMA in gamm are not useful to control the autocorrelation

I want to analyze the climate effects on the number of malair (Frequency) in several cities(region), while I find there is serious autocorrelation in residuals. However, there seems to be no ...
0
votes
0answers
15 views

Estimate VAR model from data about lags

Does anybody have any idea how i would write the var model based on this table? What coefficients should be included? Any hint will be much appreciated. Thank you!
0
votes
0answers
42 views

Estimate UCM Equation from Ucm model?

Given the output of a ucm sas procedure i need to estimate the equations from the given output , but i don't really know how to do it or where to start. Do you have any hints or anything that might ...
1
vote
0answers
26 views

Time Series data used for estimation

I am new to Time Series analysis, but I have Time Series Data. I am trying to estimate the total number of users of a product that occurred over a three month period. I have one observation of the ...
2
votes
1answer
53 views

How to calculate the cross correlation between two time series measured at different instants?

I have two time series with measurements of the same type but different stations. I would like to know if the two series are correlated and how much is the "lag" between them. The idea is that in this ...
0
votes
0answers
32 views

Identifying deterministic trend vs stochastic trend

In EViews for Augmented Dickey Fuller Test I get a p value of 0.4326 .I have few questions regarding this? 1.Does this mean I have a stochastic trend or a ...
1
vote
0answers
44 views

How to write ar & ma terms in dynamic regression/arimax in terms of actual predictors?

I have done Arimax with response series Y as sales/demand & a set of input series on time series data at monthly level. The estimates from the arimax model is as shown below. I want to now ...
2
votes
0answers
28 views

What to look for in vector time series, and how

In univariate time series, it's pretty intuitive to look for transformations to give you a stationary covariance noise component, e.g., linear or seasonal trends. And you can look at the ...
0
votes
1answer
35 views

Is there an advantage to using moving average versus removing outliers?

I have a dataset and for each hour there is 3 readings (sometimes missing and sometimes clearly an outlier). I am trying to find the mean of the entire dataset for the parameter. It has been suggested ...
0
votes
0answers
10 views

State-space model: measurement-driven steps?

I have a time series that seems to be well described by a univariate local level model (a changing bias in human visual perception, sampled at regular intervals). I have a hunch, however, that the ...
1
vote
1answer
35 views

How to choose the order of a GARCH model?

In order to model time series with GARCH models in R, you first determine the AR order and the MA order using ACF and PACF plots. But then how do you determine the order of the actual GARCH model? ...
1
vote
1answer
28 views

Identifying a stochastic trend model

My question is a bit general Say I am given a time series $X_t$, In what ways I can use in order to check whether the sequence behaves like a stochastic trend model or not? and if yes how can I find ...
1
vote
1answer
41 views

Normality of data in OLS

I am trying to perform an OLS on time series for a project for college. The professor told me that I need my regressors to be normal in order to justify the use of a linear regression. His argument ...
1
vote
1answer
71 views

Time Series: Does stationarity imply mean reversion?

I'm trying to see if a time series demonstrates mean reversion. I found two tests: Augmented Dickey Fuller Test and Hurst Exponent. However, the alternative hypothesis is that the series is ...
0
votes
2answers
79 views

Which standard deviation to use for p-value of regression coefficients?

Matlab generates regression coefficients for vector time series models ("vgxvarx"). For a given regression coefficient, the p-value is just the area under the t-distribution beyond |t| > ...
1
vote
1answer
42 views

Difference time series and then minus the mean of the differenced series within Arima

This question is similar to the following question in the sense I am currently doing the differencing and mean removal of the time series outside the Arima function ...
1
vote
1answer
65 views

Predicting Sales Over Time

I'm pretty new to including time in any sort of modeling, so forgive me if any of my questions are basic. I'm trying to predict a final sales number over a certain period of days using the ...
2
votes
1answer
34 views

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 ...
2
votes
0answers
46 views

Visualising complex data with various groups + sub-groups over time period

I have a data set that looks like the following: ...
1
vote
1answer
59 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, ...
0
votes
1answer
31 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 ...
1
vote
1answer
54 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 ...
0
votes
1answer
50 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, ...
2
votes
2answers
156 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?
0
votes
0answers
10 views

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 ...
2
votes
1answer
54 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 ...
0
votes
0answers
15 views

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 ...
0
votes
0answers
23 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 $(1-z)^{-1}$. ...
2
votes
1answer
26 views

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 ...
1
vote
1answer
27 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 ...
1
vote
1answer
240 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. ...
0
votes
0answers
26 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?
2
votes
2answers
108 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?
1
vote
1answer
22 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 ...
2
votes
1answer
31 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 ...
5
votes
2answers
115 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 ...
2
votes
0answers
24 views

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 ...
1
vote
0answers
32 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 ...
2
votes
0answers
29 views

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 ...
2
votes
0answers
33 views

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 ...
1
vote
2answers
61 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 ...
1
vote
1answer
33 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 ...
0
votes
1answer
46 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?
3
votes
1answer
77 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 ...
2
votes
0answers
34 views

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). ...
1
vote
0answers
32 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. ...
4
votes
0answers
134 views

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 ...
2
votes
1answer
60 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 ...
6
votes
2answers
160 views

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 $g(X_n) \overset{p}{\to} g(X)$. ...