Time series are data observed over time (either in continuous time or at discrete time periods).
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1answer
35 views
First difference or log first difference?
I am evaluating the effect of covariances between series on returns. That is I run the following regression: $$ r_t = \beta_0 + \beta_1\text{Cov}(Y_t,r_t) + ...$$
I have conducted my analysis with ...
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0answers
28 views
Block bootstrap for dependent data with unequal sampling intervals?
I have data from a natural archive (lake sediment). For various reasons it is usually impossible to sample the archive equally in time, and we end up with a time series where essentially we have ...
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0answers
16 views
Best practices for dealing with shifting, inconsistent seasonality
This question is related to a previous post I've looked at (Calculation of seasonality indexes for complex seasonality), but deals with more granular data (daily instead of weekly), and transforming ...
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2answers
44 views
State space models for time series forecasting
I am new to time series forecasting and have been slowly working my way through the different approaches available. I've so far mainly been using ets and arima models available in the R forecast ...
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22 views
Reconstructing time series data with missing values from external data source
I have a 100 year time series. But the first 30 years are missing. So I correlated the 70 years that I have with another (100 year) time series to predict back / reconstruct the missing values. For ...
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1answer
28 views
What is the proper name for a backward forecast?
Suppose in time series you have the data in a recent period and you would like to use that data to extrapolate backward to get estimates of the time series back in time. What do you call that? ? ...
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1answer
37 views
when to aggregate when time series forecasting
I have a some historical sales data for various product SKUs, including category information ("department" "category", "subcategory"). I want to use this to generate sales curve (a baseline forecast ...
2
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1answer
30 views
ACF and PACF of AR process with non-zero mean
Calculating the acf and pacf of an AR process with zero mean is straightforward, but does anyone knows how to proceed when the mean is not zero? Of course my intention is to calculate the theoretical ...
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33 views
Dummy variables for time series
I'm a new user on R. I'm stuck on my times series research currently with the some questions. Not sure anyone can help me.
Dummy variable.
I wanted to add more than 1 dummy variable in the model. ...
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16 views
Chow's test and serially correlated model errors
how can one handle a time series with the Chow's test (in order to find a structural break) so that the assumption of independent model errors holds? I'm using the R function chow.test {gap}
4
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1answer
79 views
Can you compare AIC values as long as the models are based on the same dataset?
I am doing some forecasting in R using Rob Hyndman's forecast package. The paper belonging to the package can be found here.
In the paper, after explaining the automatic forecasting algorithms, the ...
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1answer
60 views
First steps learning to predict financial timeseries using machine learning
I am trying to get a grasp on how to use machine learning to predict financial timeseries 1 or more steps into the future.
I have a financial timeseries with some descriptive data and I would like to ...
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2answers
112 views
Forecast total for a year given monthly time series
I have a monthly time series (for 2009-2012 non-stationary, with seasonality). I can use ARIMA (or ETS) to obtain point and interval forecasts for each month of 2013, but I am interested in ...
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1answer
69 views
How to forecast hourly data in R
I have hourly login data for a web site. Certain hours of the day for example between 09:00 and 12:00, there are heavy traffic on the site. I would like to forecast the hourly data for about one year.
...
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0answers
13 views
Is spectral leakage a random variable?
Spectral leakage is obviously a function of several factors, including its underlying algorithm, precision of variables, etc.
Is there a body of work that explores the behavior and attempts to ...
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1answer
87 views
Does this histogram of residuals indicate that the residuals are effectively random?
I am studying a univariate and discrete time series. I know that residuals should be effectively random and have a good fit, and should have a bell shape.
Does the plot below suggest that the ...
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0answers
10 views
SK test for time series comparison or alternative?
I am evaluating the ability of the data derived from keywords typed in a search engine to detect outbreaks of a certain disease, by comparing it to the laboratory data for the same data. So I have two ...
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0answers
16 views
How should I interpret the (Bartlett) lag window in this equation?
I'm trying to apply a technique for identification of structural breaks in a financial time-series (so heteroskedastic) and one of the estimators is defined as follows:
$$
\hat{\omega}_4 = ...
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1answer
42 views
What do error bounds in forecasting represent?
What do error bounds actually mean in forecasting timeseries? For example, when I get a forecast I get the 85% and 95% high and low error bounds. I can also set my own error bounds to be calculated ...
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27 views
Implementing an ETS and ARIMA forecast
I've been using the R Forecast package which I have used to create fitted ETS and Arima models. I can easily predict ahead within R using the Forecast package but need to be able to do prediction ...
4
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2answers
97 views
Data visualization of average and standard deviation over a small time series
I am trying to find the best way to visualize the following data:
I have values for 3 different times/dates, each time/date has the same 20 species. For each species I have the average height and ...
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0answers
11 views
Step detection segment
Is it possible to identify a segment (not point) of structure change within a time series? Ideally, I want something similar to a way to look at a time series and use the breakpoint function within ...
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0answers
33 views
Time Series Analysis (ARIMA) with Logistic Regression and Control variables
I'm planning to do a study on readmissions in a certain hospital unit and I want to study the impact of an intervention on readmission rate (binary variable), while controlling for individual-level ...
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1answer
34 views
How to forecast time series with the help of other training time series in R?
Consider such a task: I have the figures on last year's bookselling of a certain book store, and the information of the first half of this year too. Now I want to predict the figure at the end of this ...
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3answers
45 views
Time Series Similarity : Differing Lengths with R
I am experimenting with creating a distance matrix between time series for clustering and similarity searching. The main reference I am using is for the Similarity procedure in SAS (Paper). I would ...
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2answers
48 views
Removing seasonal and non-seasonal oscillations with least-square method
I have data on sea temperatures at different depths. With these data I need to remove seasonal and non-seasonal oscillations by fitting a function that consists of two sinusoids with periods of 12 and ...
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1answer
101 views
Time Series Forecasting with Daily Data: ARIMA with regressor
I'm using a daily time series of sales data that contains about 2 years of daily data points. Based on some of the online-tutorials / examples I tried to identify the seasonality in the data. It seems ...
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1answer
23 views
How to accurately track the 75% quantile in a non-stationary timeseries?
I have a non-stationary timeseries with a mean (µ) and standard deviation (SD) which both vary across time. The distribution of the timeseries is skewed, so the left and right sides of the ...
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0answers
21 views
Interpretation of error term in Moving Average (ARIMA)
I have an elementary question regarding the error term in MA (ARIMA)--
From where does this error term come from?
From what I understood from the question raised earlier in the following link: ...
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0answers
12 views
Adjusting mixes of categorical variables by duplicating records
I have a large table with 4 columns, MONTH, COLOR, REGION and RESULT with the results of various contests that are repeated many times each month for the different colors. I can get the result to see ...
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1answer
43 views
Is there a statistical model for modelling variables that are measured in varying amounts and in different time points per individual?
I have been trying to model a dataset of variables where each individual is measured a different number of times, and on different point in time. Most of my variables are count, but some are not (the ...
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0answers
16 views
raster images stacked recursively [migrated]
I have the following problem, please.
I need to read recursively raster images, stack and store them in a file with different names (e.g. name1.tiff, name2.tiff, ...)
I tried the following:
...
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1answer
69 views
Approaches to Forecasting with Daily Timeseries
I have just started to learn about forecasting. I thought it would be easy to create forecast models for a daily time series but have encountered a number of difficulties. Firstly most examples and ...
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0answers
8 views
Generating yearly frequency plot from multi-year data [migrated]
I have hourly wind speed data in the following format
...
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0answers
20 views
Harmonic or dummy seasonal model
Within the BFAST package in R, one of the parameters that it gives is the choice of seasonal model parameter (harmonic, dummy, or none). I understand what none does; However, I didn't really ...
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2answers
39 views
With regard to ARMA time series, what exactly is eacf (extended auto-correlation function)?
I'm going through my copy of Analysis of Financial Time Series, 2nd Edition, and I'm at the ARMA portion. One of the techniques for model selection is computation of the extended auto-correlation ...
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0answers
11 views
Mean absolute percentage error (MAPE) in Scikit-learn
How can we calculate the Mean absolute percentage error (MAPE) of our predictions using Python and scikit-learn?
From the docs, we have only these 4 metric functions for Regressions:
...
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1answer
43 views
Time series deseasonalization
How do you know when deseasonalization is not necessary? That is, from what I understand, if you want to just look at the trend and irregular components of a time series, then you just need to remove ...
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0answers
36 views
Order of GARCH model
I am Ashenafi
I would like to ask, Is it possible to know the maximum order of GARCH(p, q); value of p and q (For example, using R software)automatically?
Example: In ArchTest, I got some ...
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2answers
97 views
In R, coefficients of MA function are wrong?
I'm currently sifting through my copy of Analysis of Financial Time Series 2nd Edition by Ruey Tsay, and one of the sections involves fitting a MA model to certain data (data set is here). Here's the ...
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1answer
51 views
What do you think is the trick making ARMA/ARIMA a good method for forecasting?
I cannot say I am very familiar with ARMA (I must admit that I am kind of biased to begin with, so for a long time, I haven't tried to bother with AR/MA-like linear models).
However, for some reason, ...
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0answers
51 views
Statistical tests on the revenue data of a small business
I have daily revenue data from a small business with 6 locations. The business sells food products that range from roughly \$2.00 to \$9.00, mainly to professionals. They do over a million dollars a ...
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1answer
76 views
Why are MA(q) time series models called “moving averages”?
When I read "moving average" in relation to a time series, I think something like $\frac{(x_{t-1} + x_{t-2} + x_{t-3})}3$, or perhaps a weighted average like $0.5x_{t-1} + 0.3x_{t-2} + 0.2x_{t-3}$. ...
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1answer
14 views
Finding a correspondence between time-series elements
My problem deals in particular with time-series data about server performance, but the solution is sure to be applicable to many types of data sets. Pardon me if the answer is well-known; I don't know ...
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2answers
72 views
Predictions of a monthly temperature time series: adding noise to the predicted values
I am doing predictions on monthly temperature data for 100 years, from 1901 to 2000 (i.e 1200 data points). I want to know if the method I follow is correct because in my output, I do not see the ...
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0answers
27 views
R Packages for Panel GARCH?
Are there any packages that let me estimate panel GARCH models in R?
I have looked extensively in Google but have not found anything.
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2answers
72 views
Confidence bands in case of fitting ARIMA in R?
I want to look at the acf and pacf of my data, to identify the model for my mean equation, so I want to fit an ARMA for my mean equation and later on model the conditional variance by a ARCH/GARCH (I ...
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1answer
54 views
Fitting GEV to non-stationary time series of extremes (general stationarity question?)
I'm fitting the generalized extreme value distribution (GEV) to a series of annual maxima of variable $X$. $X$ exhibits a linear trend.
When I fit the GEV to $X$, I think I have the choice to
Use ...
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1answer
52 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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1answer
48 views
