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

learn more… | top users | synonyms

0
votes
0answers
2 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 ...
1
vote
0answers
9 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 ...
0
votes
0answers
14 views

High autocorrelation parameters? [on hold]

I plotted the autocorrelation and partial autocorrelation for two of my time series data in R. But it seems that one of the autocorrelation plots of the two has much higher autocorrelation parameters ...
1
vote
0answers
16 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 ...
0
votes
0answers
11 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, ...
0
votes
0answers
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 ...
0
votes
0answers
15 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 ...
0
votes
0answers
19 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 ...
1
vote
0answers
11 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 ...
1
vote
1answer
40 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 ...
2
votes
0answers
32 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 ...
0
votes
0answers
11 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 ...
0
votes
0answers
13 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 ...
1
vote
0answers
21 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 ...
1
vote
1answer
23 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 ...
1
vote
1answer
33 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 ...
0
votes
0answers
15 views

Creating a Volatility Index [on hold]

Edit: Is there any way to create an index that captures volatility in a time series? I'm looking at a simple way in excel preferably. I am specifically trying to create a volatility index of the ...
1
vote
2answers
50 views
0
votes
0answers
18 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, ...
0
votes
1answer
32 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 ...
0
votes
0answers
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 ...
0
votes
0answers
14 views

Nonlinear forecasting methods [closed]

Can anyone recommend a nonlinear forecasting method for time-series performance data? It doesn't depend on seasonality so Holt-Winters isn't appropriate. Edit: the data is arrears percentages for the ...
0
votes
1answer
24 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 ...
0
votes
0answers
22 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 ...
0
votes
0answers
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
votes
1answer
24 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 ...
0
votes
0answers
6 views

Shock event values in Linear Aggregate Definition of AutoRegressive Process

I am 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 ...
0
votes
1answer
15 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 ...
1
vote
0answers
18 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 ...
0
votes
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 ...
0
votes
0answers
9 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. ...
0
votes
0answers
5 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 ...
1
vote
0answers
13 views

Where can I find good references regarding to noise filtering and prediction in time series?

I want to model the error structure of every certain time period obtained from the past errors produced by the predictions of nonlinear time series. I would like to know if someone knows specialized ...
1
vote
0answers
15 views

Advice on imputation of multiple time series

Background In the first year of the study 60 streams had temperature data loggers installed (temperature measured every 30 seconds). The second year only 30 of these same streams had data loggers. ...
0
votes
0answers
8 views

Moving sum window based on the time [closed]

I have a data frame and there are two variables where one is a numeric(x) and the other is a date(t). I would like to create a new variable which will calculate the sum of X in the last time window. ...
1
vote
0answers
14 views

Multivariate binary time series

I have several concurrent time-series, which have binary response: Yi = (yi1, ... , yiT) where yit = 1 or 0 at an observed time t. i = 1, ...,n (where n is the total number of concurrent time ...
1
vote
1answer
83 views

Why can't my (auto.)arima-model forecast my time series?

For testing I generated a very simple time series with a clear recurring pattern. I expected that auto.arima will generate a model, that can forecast that pattern, but óbviously it doesn't. Can anyone ...
0
votes
1answer
23 views

Nonlinear forecasting

I'm working with time series data (which fluctuates constantly) and currently have 27 data points to forecast with. Would anyone be able to recommend a nonlinear forecasting method using formulas to ...
1
vote
1answer
34 views

Am I causing statistical violations? [closed]

I am trying to analyze where the significant differences are between 2 sets of time series. Group 1 (Expert) has 29 trials normalised to 256 points whereas Group 2 (Novice) has 19 trials (see attached ...
3
votes
1answer
49 views

Why can't we use top-down methods in forecasting grouped time series?

As I asked in here I was trying to forecast grouped time series with two grouping variables and I find some limitation of hierarchical forecasting methods. In particular, using hts package from R, we ...
1
vote
0answers
25 views

How to use Singular Value Decomposition for time series?

I want to represent a time series using the SVD algorithm. Below are some representations from this presentation. The SVD representations is formed by summing k "eigenwaves" corresponding to the ...
1
vote
0answers
17 views

Understanding changes in bookings per medical practice

I have data for counts of bookings per day. I have data for counts of active medical pracitces per day (active means that they have published appointments that are able to be booked in the past 28 ...
0
votes
0answers
19 views

Constant in arima model whether to include or exclude?

I have a very basic question on including constant in Arima models. I'll illustrate this by an example. I have the following ACF and PACF of a weekly time series that is differenced at lag 1 (trend) ...
1
vote
1answer
30 views

Work with results of tbats decomposition

I made a time series decomposition with tbats. There is weekly and yearly seasonality in the data (and maybe also monthly - not really important for the question) ...
1
vote
0answers
24 views

Online time series forecasting with DLM

I have estimated a univariate time series model, consisting of a random walk and an AR component. Now the goal is to make forecast about a couple of steps ahead as new data comes in, in an online ...
0
votes
0answers
18 views

Cox Time Series Data — Analysis of Interaction Terms

In a time series data set using Cox Proporational Hazard Rate, I am testing a model with interaction terms. I am worried that my interaction term is biased by several specifications of my model and I ...
2
votes
1answer
35 views

Recommend e-book that is comparable to Hamilton's Time Series Analysis?

(NOTE: I have read the topic re "books for self-studying time series analysis," this question is intended to be different in a very specific way, and I am looking for answers that would not be ...
0
votes
0answers
10 views

simple exponential smoothing - Ljung-Box test - residual

I'm a newbie in statistics and actually I'm studying Time Series. Reading this page (http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html) I found this sentence: ...
0
votes
0answers
23 views

Best forecast method for my data

I have a large amount of statistical data on tennis matches over the last 10 years and want to be able to forecast the percentage of points a server will win on his own serve based on past data. For ...
2
votes
1answer
35 views

Benchmarking time series forecasting model

Problem: I'm building a time series forecasting model for daily data wherein, the aim is to forecast for the next one week. So, to validate the model, I'm using a moving window based validation ...