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

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How to find the pdf from time series

This may seem trivial but I will appreciate help in determining the functional form of the probability density function (pdf) for the following case. Will highly appreciate some guidelines on how to ...
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6 views

prediction using historic data with unusual annual trends

I have 4 years of daily data. there is a decreasing trend for the data for the first 3 years but the trend increase for the 4th year. I wanted to find a fitted model using the first 3 years and then ...
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prediction for data including weekly and annually seasonality and dummy variables for holidays

I have a three years of daily data for number of orders a trucking company receives everyday. Number of orders are high during weekdays and they have a huge decrease for weekend. I used msts to ...
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7 views

wrong predictions for weekend but good predictions for weekdays

I have a set of 3 years of daily data. I saw weekly and annual seasonality in the data so I used msts time series and tbats to fit the best fitted model. the predicted values for weekdays are with 5% ...
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198 views

Test to distinguish periodic from almost periodic data

Suppose I have some unknown function $f$ with domain $ℝ$, which I know to fulfill some reasonable conditions like continuity. I know the exact values of $f$ (because the data comes from a simulation) ...
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1answer
285 views

Forecasting optimization techniques in fantasy baseball

I am currently trying to build a better forecasting model for my fantasy baseball roster. I currently am using commonly accepted projected season statistics (ZiPS from Fangraphs) to determine the ...
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15 views

predicting time series with support vector machine using R

I am planning to do time series prediction using support vector Machine. I could not find any materials about time series application of support vector machines using R or Mat-lab. Similar question ...
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1answer
364 views

How to apply an AR(MA) model to a prewhitened signal?

I have two (vehicle velocity) signals that should consist of similar "latent" drivers, but have different autocorrelation structures. The driver-signals are quite nasty statistically, so I'm not ...
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70 views

Increasing the accuracy of tbats() forecasts by factoring for correlations between different time-series?

This question builds on my previous question Forecasting Hourly Time Series based on previous weeks and same period in previous year/s. My project is to forecast the number of ~400 different types of ...
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80 views

How can i find the significance of the cointegrating coefficients in output cajorls-function in R?

I investigate the long-term relationship of some variables but in the output provided by cajorls-function, I can't see for each coefficient if it is significant? This is provided by the ...
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Time series forecasting accuracy measures: MAPE and MASE

We come to this toy example showing MAPE and MASE are not consistent when measuring forecasting accuracy. Data consist of 100 white noise and 100 $AR(1)$ time series with length $N=500$, mean $\mu=1$ ...
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83 views

How should I set up my data for classification when there is a time component?

I am assuming there is an optimal why to set up my data to achieve my goal of predicting who will retire next year. I can think of two methods. Which do you think is the most appropriate and why? Or ...
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208 views

Trying to use Holt-Winters to fit this data

I'm trying to fit the data in this message (daily temperatures) using the Holt–Winters technique in R, but can't get the seasonal example in here to work. Is this not possible with these data, or am I ...
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126 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
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15 views

Normalized RMSE

I have several time-series in a VAR(1) and, due to some of them haven't the same unit of measure, I'd like to estimate the RMSE in percentage. I know that it could be done in several ways (see below) ...
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1answer
77 views

Error Calculating MVN Likelihood of Time Series with AR(1) Errors in R

I'm having trouble calculating the likelihood of a time series with AR(1) errors. I am generating my covariance matrix according to page 2 of (http://cran.r-project.org/doc/contri...regression.pdf), ...
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1answer
33 views

Seasonal vs non-seasonal coefficients in R ARIMA

Let's say I have the two following ARIMA models: ARIMA(7,1,1) (no seasonality) ARIMA(6,1,1)(1,0,0)7 (seasonality of period 7). Are they conceptually the same? If so, why is that when I model ...
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1answer
85 views

Weighting time series coefficients using model's likelihood

I have a question regarding to time series forecasting. In particular I've been working with a Bayesian approach, but I think the question is independent from that. I have several time series which ...
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4answers
333 views

How to perform proper data mining on time-series data?

I have some daily data from city A, B, C. Values from city A are highly correlated with values from other cities for lag -1,-2,-3 and -4. I want to use Random Forest, SVM and ANN to predict values ...
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R code for time series forecasting using Kalman filter

Does anybody have a good example for Time Series Forecasting/smoothing using Kalman Filter in R?
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23 views

Standard model for time series with (possibly multiple) seasonal component

Suppose you have a "new" way to formalize a seasonal component and you want to see if your method is worth to be published. My idea is to take a "standard" model for time series with seasonal ...
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1answer
182 views

Evaluating Time Series Prediction Performance

I have a Dynamic Naive Bayes Model trained on a couple of temporal variables. The output of the model is the prediction of P(Event) @ t+1, estimated at each ...
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63 views

Does Stationarity for Time Series extend to Independent Variables?

There have been many questions about the importance of stationarity and also its means of calculation here on CV, but one question that I have not seen an answer to is whether or not stationarity (in ...
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1answer
161 views

How to initiate value for dlmModPoly?

I'm trying to build a model to predict a product's sale price. I'm researching the dlm package. Looks like I should use dlmModPoly, dlmMLE, dlmFilter, dlmSmooth, and finally dlmForecast. I'm looking ...
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73 views

Time series forecasts of appointments with pre-registration

Looking for some tips and ideas. I get a list every day of the number of appointments for each day for the next two weeks for a clinic. I have quite good history of these list, and the actual number ...
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28 views

Stock Closing price forecasting using ARIMA Model in R ( Entry level R programmer and Statistics learner)

I am an entry level R programmer and trying to learn statistics. i have downloaded the daily stock Adjusted Close price of one stock from sep 2011 to till date. As per my study plan, i have plotted ...
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64 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
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1answer
38 views

How to fit an ARMAX model with more than one exogenous time series?

I am trying to fit an ARMAX with two exogenous time series with the following code but it gives me an "computationally singular" error. I know it is about defining more than 2 time series for ...
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299 views

Updating classification probability in logistic regression through time

I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
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1answer
44 views

Validate a Markov Chain with few states (model switching)

Suppose I have a five state Markov chain. The states are observable (in fact I defined them, they are outcomes of an classification algorithm). So I have a long time series, see the first picture. ...
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69 views

How to best make millions of forecasts using time series data?

I need to make roughly 50 million forecasts every night. The data is daily, hierarchical (~50 million base series), intermittent/sparse (for many of the time series, lots of days have 0's), and not ...
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1answer
36 views

Transforming a time series with a negative number

I have been given data to forecast however it has a negative figure within the data which then, when doing a log transformation to make the series stationary, the ARIMA script i have written won't ...
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3answers
91 views

Forecasting: Different Model for 1 month, 2 month, 6 month forecasts?

I'm still trying to expand my statistics and forecasting technique knowledge. Right now I'm forecasting seasonal contact patterns, so the simplest model I can understand with seasonality is a ...
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244 views

Correlating time series for 20 regions (SPSS)

I have a question to which I can't find an answer although I spent really awfully lot of time searching. I have time series data for about 20 regions of a country. Each time series covers 20 years. ...
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125 views

How to estimate model with both linear and exponential parameters?

I have a theoretical growth function that can be perturbed by events, and I'd like to estimate the growth parameters as well as the perturbation, and the rate of falloff after that perturbation. I'm ...
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1answer
468 views

Transfer functions in R (TSA package)

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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26 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
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70 views

Statistical methods for analysing correlation between stock price index and natural disasters

Can someone help me identify what statistical method (or any method) that I can use to correlate the effects of natural disasters on Stock Market Index?
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Detecting a step change in time ordered data

Suppose I have data which looks like this: ...
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regression test or two bloc PLS model to prove a gene expression matrix relationship

I have two gene expression matrices, matrix A coming from a set of two hypothetically different cells while matrix B is coming (for certain) from only one of them. The structure of a gene expression ...
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1answer
20 views

Data with weekly and annually seasonality but the first day in time series is not the begining of a week

I know it might look naive but I have a very basic question. I have a three years of historic data which has weekly and annual seasonality. January first as my first data is on Wednesday so my time ...
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4answers
189 views

Forecast accuracy calculation

We are using STL (R implementation) for forecasting time series data. Every day we run daily forecasts. We would like to compare forecast values with real values and identify average deviation. For ...
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2answers
37 views

Problem in ARIMA Model in R

I am running ARIMA model in R and I used auto.arima(X) function to decide appropriate model.After using this function I found that the order of my model is ARIMA(2,1,0). The problem is I run the same ...
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1answer
42 views

Difference between the forecast and simulate functions in the {forecast} package in R

I have been using the forecast package in R to make forecasts based on an ARIMA model and have noticed a difference in the output of the forecast and simulate functions when calculating confidence ...
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278 views

ARIMAX and xreg variables

Just wondering how to setup xreg variables for ARIMAX models? I am particularly interested in whether I should be grouping together events for dummy variables. For example should I create 1 dummy ...
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36 views

No fitted ARIMA model

I wanted to fit an ARIMA model to a daily database for three years but auto.arima couldn't find a model and showed the following error: ...
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71 views

ARIMA, adjustments and intervention analysis

I have very little knowledge of time-series analysis (despite my stat master - didn't do anything else than an introductory course) but now I'm facing a statistical problem whose answer is this very ...
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2answers
124 views

Comparing categorized data

I am quite rusty on my stats beyond standard deviation and linear regression, so I am not even sure about how to phrase this question. I am looking at a long history of credit card qualification ...
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1answer
68 views

Forecasting a seasonal time series in R

Forecasting airline passengers seasonal time series using auto arima Hi, I am trying to model some airline data in an attempt to provide an accurate monthly forecast for June-December this year using ...
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104 views

Does it make sense to use dynamic time warping when clustering time series that all have the same length and sampling interval?

Comparing Euclidean distances with dynamic time warping (DTW): Will Euclidean distance perform better than DTW when clustering time series that all have the same length and sampling interval? Are ...