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

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117 views

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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3answers
649 views

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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115 views

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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1answer
2k views

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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0answers
70 views

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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2answers
4k views

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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2answers
178 views

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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1answer
1k views

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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3answers
3k views

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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0answers
51 views

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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1answer
114 views

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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3answers
730 views

Question about eliminating seasonality

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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0answers
91 views

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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4answers
9k views

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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0answers
110 views

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 ...
2
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3answers
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 ...
2
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1answer
93 views

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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0answers
56 views

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 ...
2
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1answer
6k views

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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2answers
228 views

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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1answer
132 views

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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1answer
268 views

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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1answer
300 views

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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1answer
111 views

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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36 views

Autocorrelation $p^2(1)<\frac{p(2)+1}{2}$

I'm struggling with a problem how to show that stationary AR(2) process autocorrelation: $p^2(1)<\frac{p(2)+1}{2}$ My solution attempt: Because $p(2)=\phi_1p(1)+\phi_2p(0)$ and $p(0)=\frac{...
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2answers
208 views

How is Hyndman's explanation of proper Time Series Cross Validation different from Leave-One-Out?

Hyndman's great explanation of proper time series CV is at the bottom of the page in the following link: http://robjhyndman.com/hyndsight/crossvalidation/ Leave-One-Out illustration in the following ...
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1answer
211 views

Time series data analysis - determining significance between treatment and control

We have some time series data for evaluating the effect of a drug in an animal model, with two dose levels and a control. So far we've looked at ANOVA for each time point, and there's a significant ...
2
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1answer
1k views

Forecasting using Holt-Winters technique using R with less than 2 years of history

I need to do forecasting of weekly sales using Holt-Winters technique. My data have max 92 weeks of information. I'm planning to consider 72 weeks of data for training & 20 weeks of data for ...
2
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2answers
333 views

Best way to visualize predictions from a linear model

Let's say I'm doing some predictive analytics and am trying to predict US GDP per month using a two or three month lag. After every month, I generate new predictions and am able to compare my ...
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2answers
812 views

How to calculated Confidence Interval for autocorrelated and lognormally distributed data?

My data is autocorrelated and is lognormally distributed, how can I calculate Confidence interval of that set of data?
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0answers
135 views

Estimating a VAR model with variable coefficients

I want to estimate a VAR model based on the Dufour and Engle paper "Time and the Price Impact of a Trade" (2000). There, the parameter $ b_{i} $ of the endogenous variable $ x_{i} $ is dependent on ...
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0answers
82 views

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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1answer
390 views

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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1answer
65 views

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 ...
2
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1answer
3k views

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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1answer
1k views

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 ...
2
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1answer
130 views

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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1answer
306 views

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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0answers
71 views

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 ...
2
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1answer
5k views

Interpreting coefficients of first differences of logarithms

My problem is interpreting coefficients of such time series model: \begin{equation} \ln Y_t - \ln Y_{t-1} =b_1 \cdot \left(X_{t}-X_{t-1}\right)+b_2 \cdot Z_t.\end{equation} I don't know how to ...
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1answer
822 views

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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0answers
123 views

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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1answer
129 views

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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0answers
32 views

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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1answer
571 views

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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1answer
465 views

How do you do time series cross-validation using python? [closed]

Also, any tutorials/blogs available that you are aware of?
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2answers
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 ...
3
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1answer
959 views

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 ...
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1answer
95 views

Probability as a dependent variable in a time-series regression

Are there any issues to run a Newey-West time-series regression on a dependent variable that is a probability? What are the biases that I am facing? I can't find anything online that can help me out ...
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0answers
690 views

Outlier detection and smoothing for multi dimensional time series

From kinect depth images, I have collected the following time series that represent the features = 3D joint positions, quarternion angles, difference between hip joint and centroid of the right arm (...