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

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Regression or time series?

I need to predict the sales of a product P2. I have access to: 7 months of sales history 26 months of sales history of another product P1 I assume the sales trends are similar because the ...
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1answer
38 views

What techniques can be used to predict a time series with another time series?

What techniques can be used to predict a time series (say monthly economic data) with another time series (say a company's sales)? If you only have about 50 data points of monthly data, and a yearly ...
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36 views

How to determine stationarity, mean and covariance?

I'm having some trouble with some questions for an assignment that I need to do. The question asks to determine whether or not a process is stationary and if it is, what is its mean and covariance. ...
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39 views
+50

How to train radial basis function for function approximation?

There is an Autoregressive model of order 1 (AR(1)) that is excited by a non-linear signal as the input: $$x_t = \rho x_{t-1} + u_t \tag{1}$$ The time series $u_t$ is generated from a Mackey-Glass ...
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89 views

Moving Average (MA) process: numerical intuition

This forum is full of questions regarding MA processes; for instance: Confusion about Moving Average(MA) Process. There seem to be a lot of confusion wrt MA processes. I think having a numerical ...
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1answer
49 views

Variable selection in time series data

I have an econometric dataset, 50 observations of 350 variables. They include things like GDP, unemployment, interest rates and their transformation such as YoY change, log transform, first ...
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1answer
54 views

How to determine efficiency of something?

What data I have? Number of causes for events, number of events, monetary value of each event, grouped by some trait. Ex. 10,000 visits, 50 purchases, each purchase €5-20, grouped by stores. What I ...
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0answers
32 views

Choosing appropriate lag length when AIC, BIC keep falling?

I'm trying to test for g-causality between a number of variables and of course I have to specify a lag length there. So, till now my approach was to test a number of lags simply (say, 1 to 30) and ...
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1answer
86 views

which book can help me for self-learning VARIMA model?

I want to understand how working VARIMA model. I spend lot of time searching some articles about time series which can show me pictures and simple description, because formulas unachievable for me. I ...
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5 views

Calculating and comparing amplitude and phase

I have data from a biological experiments of two groups, Observed over time, that looks like this: I'm looking for a way to calculate and compare both the amplitude of the "waves" and their phase ...
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40 views

Can I use Adaptive MCMC in any setting?

In time series econometrics and finance, most Bayesian authors approximate their models with a Gibbs Sampler, this is especial true for state space models, SV and so forth. The dimensionality of ...
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24 views

Methods to find the correlation between one variable and a set of variables

I have discrete measures (let's say $I(x,y,t)$, i.e., coordinates in space and time) on a geographical map that are sampled randomly. I also have a constant flow of optical images in several ...
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18 views

comparing multiple proportions over time

I have a dataset of 22 fish species in a fish market, sampled monthly, from 2007 to 2011. I want to see if there is a statistically significant change in their relative proportions over time. I first ...
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33 views

Can we estimate VAR model using monthly data for 7 years?

I am interested in estimating the long run relation between electricity shortfall and industrial output with other variables. It forms a 6*6 matrix. Can I get reliable estimates? I am very much ...
3
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1answer
53 views

GARCH vs SV for Forecasting

I believe I am aware of how GARCH family and stochastic volatility models differ in their construction and assumptions on the volatility states, (i.e. GARCH family assumes deterministic volatility ...
1
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1answer
19 views

A smoothed series still exibits strong seasonality

I have a monthly time series. It is basically a price level series (inflation data), and I converted it into monthly percentage changes (i.e. like the CPI measure). This time series exhibits extremely ...
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1answer
203 views

How can I recognize when I must apply “log transformation”?

I have some time series - http://ww2.coastal.edu/kingw/statistics/R-tutorials/simplenonlinear.html In this article author try to use log transformation for pressure data. How can I recognize that ...
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0answers
115 views

Estimation on evolving distribution with small updates

I have a set $X$ of $10^6$ elements and a time series of probability distributions $\mu_1,\mu_2,\ldots$ on $X$. I want to estimate the expected value of a function $f$ over each $\mu_t$. It is easy to ...
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3answers
115 views

Distribution of White Noise in Time Series

I'm a math graduate student and I have to use time series in my thesis. I have not so much knowledge in statistics, but I've studied about probability and time series. So my question maybe can be very ...
2
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1answer
73 views

Is an auto-correlation plot suitable for determining at what point time series data has become random, and how does one interpret the plot?

A piece of research I am working on requires us to decide at what point time series data has become random. For what it is worth, the time sequence in question is a collection of in-process timings ...
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26 views

Consistent estimate vs out-of-sample performance

When there is a cross-correlation structure in linear regression errors, the usual approach is to model the errors as an ARIMA process. It leads to a consistent estimate of the parameters of the ...
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0answers
7 views

Can Hurst Exponent be applied to non-stationary series?

I have a set of non-stationary time-series which I want to model with ARMA models. Can I apply the Hurst Exponent to the time-series or should I apply it to the differenced time-series (assume ...
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1answer
25 views

Standardised residual No Arch Effect

I'm working with bond data and I want to get standardised residuals to conduct a copula analysis. The problem is that often the prices, for consecutive days, are the same and this fact makes the log ...
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17 views

Does a high autocorrelation imply high predictability using an AR model?

Assuming that I have a list of time-series which all have significant autocorrelation at lag 1 and no significant autocorrelation at any other lags. So if I want to test for the predictive abilities ...
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15 views

Evaluating a proportion over time

How do I evaluate a proportion within a population over time? For example, a group of patients undergoes an intervention. Assessment of knowledge is obtained pre-intervention and post-intervention, ...
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6 views

Restarting Lag based on Change in Name in Different Column [migrated]

I am trying to insert lags of a variable into a separate column in my data frame on R. However, I want the lags to 'restart' every time the name in a different column changes. An example of data is ...
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23 views

Calculating the optimal Holt Winters parameters (not in R)?

The Holt Winters (HW) technique requires the following parameters: Alpha, Beta and Gamma. The accuracy of the forecasts depends on these parameters. Some software packages (like in R) are able to find ...
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21 views

How should I interpret the results of these two models?

I have a panel data set with two time points: t and t+10. I first ran cross-sectional models for data at t and t+10 separately Y = a + bX b is statistically significant in both models, indicating X ...
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13 views

How should I test for multivariate GARCH effects for residuals of a model?

I would like to test the multivariate GARCH effect of a multivariate time series. The multivariate Ljung-Box test can do this. However I am also looking for a test to show that a DCC or CCC model can ...
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1answer
50 views

Does ARIMA require normally distributed data? [duplicate]

I want forecast inflation using ARIMA model. My questions are: Does ARIMA require normally distributed input data? (Because my data—inflation—is not normal.) If ARIMA require normally ...
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45 views

What is a test that I can use to determine if a time series is first-order stationary?

I need to test that one of the time series in my analysis has a constant mean over time. Is there a standard test I can use to help me determine this? I know that I can use a nonparametric procedure ...
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14 views

Multiple event for segmented regression?

Is there any statistical methods like segmented regression for many(>3) events? Recently, many policies in my field were introduced in a short period of time. I usually used segmented regression to ...
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22 views

How to Find the Correlation in Time Series of Categorical Variables in R?

I have a data set of categorical variables occurring weekly. A sample dataset can be found in my previous post. I want to check the co-existence of these categorical variables over time. I want to ...
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29 views

What are some tests for the predictability of time-series?

I have 2500 time series which I want to test the predictability and based on that, choose the best one to forecast. Ideally I want to use a simple model like ARMA-GARCH for forecasting. Are there ...
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1answer
33 views

Multi-step ahead forecasting with Weighted Moving Average?

The Weighted Moving Average method is usually used for smoothing purposes. However, it can be used to forecast $Y(t+1)$ based on the last n observed data. In real-world problems, forecasting in very ...
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1answer
43 views

On estimating ARIMA models on artificially made time series data

For each day, I observe my variable, y(t), for a period of 12 hours. In order to understand the data and make predictions, I want to put together these data and ...
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62 views
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28 views

ARIMA versus a Mixed model for trend detection

I am trying to find any evidence of warming in monthly times series data of water temperature over a 21-year period that is serially correlated. Essentially I am looking to determine a global trend, ...
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1answer
39 views

Time Series Data and SAS

I have a time series data set with 54 observations. I need to use the SAS software. I am aware that I can create a dataset in the SAS library and then open it. however i am not able to open the data ...
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25 views

FORECASTING AR(1) Autoregressive Form

Ive been implementing a little exercise to obtain the first 2 forecasting points of an AR(1) process. And i want to have the forecasting ponts using the three forms: Im folowing this pdf ...
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1answer
30 views

Multidimensional dynamic time warping

I am trying to understand how to extend the idea of one dimensional dynamic time warping to the multidimensional case. Lets assume I have a dataset with two dimensions where ...
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35 views

Prediction over the time with cohort

I'd like to modelise the evolution of the sales of a store. Here are the date I have : i.stack.imgur.com/6FsZ8.png -customers are aggregated into monthly cohort depending on the date of the first ...
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16 views

Need advice on unbalanced time-series dataset, for use with CAPM regression

I have 40 years of monthly historical returns of around 3000 mutual funds. The dataset contains both active and inactive funds, so some funds have data for the whole period, whereas others will have ...
0
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1answer
33 views

Confusing results on kpss.test() for stationarity

I've got a dataset which clearly shows a trend. However, I want to assess wether this trend is deterministic or stochastic. If I understood it right, I would need to use differences if the trend is ...
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11 views

Shock event values in Linear Aggregate Definition of AutoRegressive Process

I am a beginner in Time Series and studying (self study) at the derivation of the relation between AR process of Deviations and the Linear Filter process of actual values of Time Series. Have this ...
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1answer
25 views

Are the data stationary or non-stationary and seasonality?

I want to use Arima model for forecasting wind speed.I plot my data. Then i plot ACF and PACF. I used ADF test and KPSS test and they said that data are stationary and doesnt need differencing but ...
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21 views

Structural Break - Stata

I have used Stata to run a time series multiple regression. I know that there is in fact a structural break in the data and the point at which it occurs; therefore, I have estimated the regression ...
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0answers
23 views

moving average: applied to time series equation

If I have an equation representing a time series, such as the following $$y(t) = y(t-1) + y(t-2)$$ But I am not given $y(t-1)$ or $y(t-2)$, so hence this recursive function is not given any initial ...
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13 views

Extensions of bsts and CausalImpact to non-Gaussian exponential family distributions

The bsts and CausalImpact packages implement a state space time series model with an optional regularized regression component. ...
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8 views

Estimate of local slope (or tendency to “correction”) in time series

I have multiple time series of values aggregated at the weekly level. In short, I'm interested in finding local estimates of slopes for each week for each time series. An example of one of my time ...