# Tagged Questions

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

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### Sampling from a dynamic population

I need to create a sample of a given size from a population. However, the population is dynamic, that is, comes as a stream of items, and every item has a "time stamp" based on its location in this ...
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### What can I do with these two time series?

Info: Blue line is the official inflation statistics by US Bureau of Labour Stats Red line is by independent researchers who claim to have created better way to measure inflation Blue line has been ...
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### Linear model or component analysis on timecourse data

I have some timecourse data which plotted looks like the figure below. I want to better describe the difference between the two conditions. My adviser advised :D me to use a linear model and observe ...
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### Linear/Non-linear Regression - SPSS

Hopefully somebody will be able to shed some light on my SPSS problems! I have been given 65 values. 57 of these data values are quarterly results and 8 are the holdback data to be used. I have to ...
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### are there any nonparametric forecasting methods?

Are there any good statistical non-parametric forecasting methods besides machine learing methods like neural netwworks/decision trees etc. for time series analysis ? If so, are there any R packages ...
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### What are the assumptions of ARIMA/Box-Jenkins modeling for forecasting time series?

What are the assumptions of ARIMA/Box-Jenkins modeling for forecasting time series?
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### What is the real meaning of null hypothesis in unit-root test for a AR(p) process?

There are functions in R (e.g., PP.test and adf.test) which have null hypothesis of unit-root in the process ($H_0$: there is a ...
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### Estimate single ARIMA for multiple timeseries

I have two groups of time-series, each group represents one type of data. However within each group, each time series may be fitted with a different ARIMA(p,d,q) from the other time series in the same ...
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### Unit root tests: how to decide if to include a trend and/or a constant

Applying a test to univariate time series data for checking if the series has a unit root or not, one is faced with a decision if one would like to test if the series is stationary around a constant ...
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### Alternative ways to define markov chain states?

I have a time series of daily measurement data, if you plot the histogram of the data points of the time series, you see long tail and high positive scewness. Also zero values is an important state. ...
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### How to analyze data which might come from a few normal distribution concatenate together in order?

For example, I have a series of values for example like the following: data <- c(rnorm(10000,40,1500),rnorm(9000,-35,1400),rnorm(11000,30,1300)) I don't know ...
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I am trying to remove seasonality from data. I tried the non-linear trend using the code: trend=lm(NH3cH6~t+cos.t+sin.t). The plot was shown as following: However, as you can see, the second peak of ...
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### rain cloud radar image prediction

I have a small pet project, which evolves around predicting a radar image of rain clouds given past radar images... My data comes from the radar images on following site: http://www.dmi.dk/vejr/...
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### Extract BIC and AICc from arima() object

Problem: I would like to extract the BIC and AICc from an arima() object in R. Background: The arima() function produces an output of results, which includes the estimated coefficients, standard ...
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### EMD-SVR method for time series

Has anyone attempted to use Empirical Mode Decomposition(EMD)-Support Vector Regression(SVR) in nonstationary time series forecasting? It seems quite interesting. As I observed it has high performance ...
2k views

### Non-Stationary Time Series Forecasting

Suppose I have a non-stationary limited data. Do I have to make it stationary before making forecasts? Can I use exponential smoothing, moving averages or even Holt Winters methods without making my ...
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### Can this be modelled?

Context: USA economy Background: Its generally accepted that the growth of e commerce has certain curbing effects on the CPI-inflation. Because search costs are much lower online, people always go ...
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### Comparing Twitter Trends on a Monthly Basis?

I'm trying to compare the frequency of a keyword is mentioned on Twitter in a monthly basis (e.g.: how many times the keyword "MissWorld" appears on September, how many it appears on August, how many ...
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### Pandas Statsmodels Time series seasonal forecasting

Using Stats models and Pandas (and requests for the data) I'm working on a forecast model.. my 1st step is just getting the Arma function working and understood. My data is available publically and is ...
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### Does Sampling Frequency matter for Time Series analysis?

I am given two time series of prices between 2009 and 2013. Price series A is weekly data, series B is monthly data. I would like to compare some basic descriptive statistics of these two time series ...
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### How can I analyze “win rate” over time (i.e. on/off data over time)?

I have a series of data points that consist of 1) a time, and 2) a win or a loss. I would like to be able to determine the aggregate win rate for particular time periods, and graph it. For instance, ...
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### Regression with ARMA errors for explanatory purpose

I have web log analysis data (AWStats) from a university library website. I'm looking at the number of visits per month divided by the number of faculty plus student enrollment (visits per headcount). ...
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### Holt Winters for multiple customers and output with R

I've been working through the HW work in the online book A little book of R for time series analysis, and have started testing with some "live" customer data. I have a dataset that looks like: ...
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### Regression on time series and its segment series

I want to test whether segment series explains anything in additional to the full series. Let's say y and ts_full are time series with same length. And I divide ts_full to 3 non-overlapping sub time ...
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### Does this autocorrelation plot look correct?

I have time series data that looks like this and I'm getting an autocorrelation plot for this time series as That is zero autocorrelation for every lag. But this would mean that the time-series ...
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### Diagnostic for VAR model. non normal

I have some problem about my model. my model is based on VAR. (vector auto-.) well, I've tested ARCH test, BG test(autocorrelation p) and jarque.bera.test. Model is stable. Also I got good result for ...
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### How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
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### GLM with Temporal Data

This is my first post on here, looking for some help. I am relatively new to analysis of temporal datasets. I have experience with R and developing linear models, so I am trying to figure out if the ...
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### What is the minimum historical data/sample data required for a time series forecasting analysis?

Are there any statistical power analysis/sample size deteminations methods for time series data analysis/forecasting? For example if I have time series of 30 data points, how can I with confidence ...
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### Detecting outlier cash movements

If I'm watching a series of accounts for transactions going in and transactions going out, I want to notice unusually large or transactions for any particular account on any particular day. So if ...
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### Time series as cross-sectional data

I have time series, for example, gdp and unemployment(unemp), freq= 4. What if I interpret it as cross-sectional data and do cross-sectional analysis instead of ...
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### Inverse correlation of time series data

I have 3 hourly power generation data for around 600 locations for a year. (i.e. 8 data per day for 365 days for each location.) I want to find out a way where out of this 600 locations, I can say ...
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### Interpreting coefficients of first differences of logarithms

My problem is interpreting coefficients of such time series model: $$\ln Y_t - \ln Y_{t-1} =b_1 \cdot \left(X_{t}-X_{t-1}\right)+b_2 \cdot Z_t.$$ I don't know how to ...
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### Modeling time: Probability distribution over time?

I'm trying to model users' posting behavior during a day. Say we have a bunch of users, with the time they post tweets. Now, for each user, I would like to estimate the likelihood of he post a new ...
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### Interpreting a regression modeled on twice differenced data

I have built a OLS model with data that was twice differenced. As I understand (and maybe I'm wrong) the coefficients (betas) can be applied to the original undifferenced data to provide Y at that ...
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### How to obtain the model behind a simulator?

I am looking for an useful statistical approach or analysis tool in order to understand the data obtained from an aeroelastic simulator of wind turbine dynamics. In this case, the simulation provides ...
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### What is the impact of windowing function on time series

Greeting I would like to know what is the impact of windowing functions like Hanning,... on a time series. Is it possible to finde anomalies using windowing functions? EDIT I have a time series, ...
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### Auto-Regressional & Moving Average Model Formula Properties

I seeking help in understanding specific values underlying the formula's for the MA(p) model & the AR(q) model. I am attempting to implement the models (building up to the combined ARIMA model) in ...
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### How do you do time series cross-validation using python? [closed]

Also, any tutorials/blogs available that you are aware of?
962 views

### Using nls() function in R for exponential function

I know that this issue was already discussed here but I faced with the problem I can't solve. I have list of persons, each represented with some time series consisting from 4-8 points. I want to ...
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### Transfer functions in R (TSA package) [closed]

In Time Series models’ transfer functions there is a decay parameter in the formula (let’s call it b). In TSA package that decay parameter is not mentioned. When I used other software before (such as ...