3
votes
2answers
64 views

What are some methods for generating simulated time series data for use in modeling?

I have a data set which consists of 50 observed years for which I have date and inflow values between a river and a reservoir. The data is formatted as follows: ...
1
vote
1answer
90 views

What econometric model to forecast a seasonal commodity demand while incorporating exogenous Information?

I have a monthly commodity demand and try to forecast this series for the next 5 years. Here is a plot: Of course, the natural approach to forecast this seasonality would be some kind exponential ...
6
votes
1answer
75 views

When forecasting sequential data is it best to use auto-regressive models or build a more traditional n x p dataset with features?

I'm familiar with the use of auto-regressive models when it comes to forecasting a single vector of time-series data. Is anybody familiar with a more traditional modeling approach, i.e. - creating ...
0
votes
0answers
7 views

Is there enough information provided? If there are serial correlations, build a mean equation for the log returns

If there are serial correlations in the data, build a mean equation for the data. As shown in the below figure, the PACF and ACF are basically identical. How ...
5
votes
1answer
153 views

Hidden state models vs. stateless models for time series regression

This is a quite generic question: assume I want to build a model to predict the next observation based on the previous $N$ observations ($N$ can be a parameter to optimize experimentally). So we ...
0
votes
1answer
92 views

Forecast Daily Data with Multiple Seasonality [duplicate]

I am new to the field of time series forecast and trying to build a time series model on R for a daily data, which I think there are multiple seasonality, weekly and monthly. My data contain the ...
1
vote
0answers
307 views

Time series modeling with R on weekly data

I am trying to do time series modeling and forecasting using R based on weekly data like below - ...
0
votes
1answer
52 views

Modeling techniques for dichotomous data

I have dichotomous data where some of my independent variables are categorical, some are continuous and some are binary (0/1). My dependent is a binary response (Fail/NoFail, 0/1). The data is some ...
1
vote
1answer
56 views

Detecting 'causality' in Likert-time series data

[Note] I've decided to re-write my question for the sake of brevity. The original question can be found below. Suppose a number of individuals fill in a questionnaire at a multiple number of time ...
1
vote
1answer
107 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 ...
0
votes
1answer
56 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 ...
0
votes
1answer
125 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 ...
1
vote
2answers
709 views

ARIMA (0,1,1) or (0,1,0) - or something else?

I've just started learning time series so please excuse me if it's painfully obvious; I haven't managed to find the answer elsewhere. I have a data series showing a pretty obvious trend although it's ...
0
votes
1answer
47 views

How to determine what method is being used?

I was wondering what time series model would forecast future values in such a static but decreasing manner? ( I'm talking about the values around where the circle appears, as apparently, the data set ...
1
vote
0answers
48 views

Comparing spatial patterns to on-average-distribution by averaging intervals that overlap in space

I am analyzing spatial patterns in vegetation structure across vegetation transects. I broke transects up into 3-m intervals that move across the transect (a moving window) 1-m at a time. So, the ...
1
vote
1answer
124 views

How to model multivariate time series

I have a set of $n=1000$ samples of 4 dimensions (multivariate) where each measurement obtained from GPS tracking data is taken at a time interval representing spatial coordinates $(x,y)$, velocity. ...
3
votes
1answer
93 views

Clustering of count data

I am currently trying to find clusters in a data set that looks like this: ...
0
votes
0answers
61 views

Non-stationary time series modelling - Product lifetime

I would have a question concerning the modeling of a non-stationary time series. I do know some of the models for stationary time series such as AR MA ARMA ARCH or GARCH, but what if the time series ...
1
vote
1answer
64 views

How to correctly model noise?

Assume a linear mixing model $x = As$, where $x = (x_{0}, ..., x_{n})^T$ are linear mixtures of $s = (s_{0}, ..., s_{n})^T$, and $A$ is the mixing matrix. Now, if I introduce additive noise to this ...
0
votes
3answers
2k views

Identify seasonality in time series data [duplicate]

I want to detect presence of seasonality in time series data. I know one can achieve that by plotting the autocorrelation function but I need an automatic process if the series is seasonal or not, ...
0
votes
1answer
102 views

Modelling two correlated variables

I wish to simultaneously predict two correlated time series. Here is a plot of one time series against the other: At the moment I have separate linear regressions for both of them which rely on ...
1
vote
3answers
160 views

What model can I use to describe the following time-series?

I'm wondering if someone might be able to help me locate an appropriate model for the following two time-series (the cyan and blue one, the reds are rolling means). I'm looking more for a general ...
0
votes
1answer
143 views

Trying to fit a model after detrending

I have data for Hydrogen Sulfide Series, see here http://www.wikiupload.com/Y4WAZJ4Z0IMTK7V I applied a Box-Cox Transformation with $\lambda =1/3$ to try to stabilize the data. I plotted a few sample ...
1
vote
0answers
33 views

Pattern of events that leads to a goal

I am not a statistician, so go easy on me here... I have collected lots of data on the behaviour of customers in a shop. A customer will enter the shop and a series of events will then take place ...
0
votes
2answers
673 views

Time series prediction - what is Autoregressive Tree model ? (Python)

Our problem: model evolution of values of a continuous variable over time. I came through a paper presenting an approach for predicting the next values for a time series. Whereas ARIMA model is more ...
1
vote
1answer
2k views

Seasonal differencing in Arima function in forecast package in R

I just want to ask about the Arima function in forecast package. The usage of it is, ...
0
votes
0answers
117 views

Analyzing online sales where data are only produced when the sales is made

I am trying to model data on the number of online sales are made within a fixed sale period of 3 days. Data are generated only when the sale is made. I think for this kind of data I will be using a ...
5
votes
3answers
845 views

What model can be used when the constant variance assumption is violated?

Since we can not fit ARIMA model when the constant variance assumption is violated, what model can be used to fit univariate time series?
3
votes
2answers
225 views

How to model market share or a fraction of anything that sums to 100%?

Suppose we have sales of 3 products A, B and C which market share always sum up to 100%. How to model market share of product A using market shares of B and C? So that we will know that if share of A ...
3
votes
1answer
177 views

How to fit a time series model for a large dataset?

I need to compare the accuracy of time series modeling and neural network techniques. As we all know, large data set is needed for neural networks. Since I'm comparing both techniques, I have to ...
3
votes
0answers
92 views

Time series modeling the number of users of a mobile app

I want to model the number of users of an mobile app. This app has two kinds of users: free and paid. I thought of this autoregressive model: $x_t = Ax_{t-1}$ with $x_t$ being a 4-dimensional ...
1
vote
1answer
93 views

Is there a non-parametric test for whether a series' unconditional variance has changed over time?

I'm not sure how this would look. It seems you've have to specify regime breakpoints within the data, right? Or is there some rolling method that could compare window sizes against each other? Also ...
4
votes
3answers
239 views

What model should I use for this research?

I am currently working on a project dealing with time series data but I have little experience with time series analysis so I was hoping to get some direction on what kind of exploratory data analysis ...
3
votes
2answers
508 views

Understanding forecasting in R

I am presently trying to learn R. I would like to be able to apply it more in my work environment as I am an analyst in the Health Care industry. I am presently trying to use R to forecast. What is ...
1
vote
0answers
49 views

Modeling a TAR model that can handle the problem of outliers in nonlinear data

Can somebody please share idea on how I can model a TAR model that can handle outliers in nonlinear data? I need to compare such model with the general form of TAR model. Which computer software can ...
5
votes
1answer
202 views

How to use statistics to help buy a house?

Despite the title, this is a more general and clearly solvable problem, I just can't research it because I have no idea what it's called. Assume you are trying to buy something (such as a house) ...
4
votes
1answer
112 views

How to handle changing definitions of regions over time in data?

I just found out that my dataset is a lot messier than I expected and I was wondering if anyone here had some advice. I have sales data that is divided into regions (5 big breaks on a national level ...
0
votes
4answers
179 views

What fields use modelling for analysis of a single time-series?

What fields of science (social or physical) use modelling for time-series analysis? In particular, time-series that cannot be replicated? Two examples that I can think of are climate modelling, and ...
1
vote
1answer
150 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
10
votes
3answers
8k views

How to fit an ARIMAX-model with R?

I have four different time series of hourly measurements: The heat consumption inside a house The temperature outside the house The solar radiation The wind speed I want to be able to predict the ...
1
vote
1answer
76 views

Disagregating overall growth into contributing factors

I have a dataset with library document holdings per publicationyear, which I can query for the frequency of terms, subjects, etc. That allows me to construct times-series of the "popularity" of ...
4
votes
3answers
499 views

Forecasting time series based on a behavior of other one

Apologies for this vague and unclear question, I have no background in statistics. I have two vectors of time series data, covering a six month period. The data is in daily intervals (except for ...
1
vote
0answers
504 views

How to model categorical (discrete-valued) time series?

Just want to make a little survey, What are, according to you, the best approach to model categorical time series? I'm building a model able to generate time series reproduicing the characteristics ...
5
votes
2answers
2k views

Using k-fold cross-validation for time-series model selection

Question: I want to be sure of something, is the use of k-fold cross-validation with time-series is straightforward, or one need special attention before using it? Background: I'm modeling a time ...
4
votes
0answers
360 views

How to model time-varying correlation

Suppose I have two time-series variables, $\{x_t\}$ and $\{y_t\}$, where $t\in[1,T]$. I would like to model the correlation $\rho(x_t,y_s)$ as some function of $t$,$s$, and the difference $t-s$. In ...
2
votes
1answer
165 views

Model the proportion of a subset of total counts to determine the difference

I've been working on solutions to my first unanswered questions and had been proposed to rather model the proportion of total count of deaths that are unnatural death counts. The reason why I want to ...
3
votes
2answers
391 views

Constant term in time series econometric models built on 1-st differences

Both dependent and independent variables I deal with are nonstationary series that become stationary after differentiating them once. The problem is that I assume that the dependent variable has a ...
2
votes
1answer
463 views

Time-series data pre-aggregated into non-stationary rolling 12-month periods: are there special considerations for modeling?

I'm exploring the use of changepoint detection or other methods (am slowly becoming aware of wavelet transformation, etc. but have tons to learn in this area) to identify key shifts in health care ...
6
votes
1answer
955 views

Why does AIC formula in R appear to use one extra parameter than expected?

I'll use an example so that you can reproduce the results ...
10
votes
5answers
996 views

When to use multiple models for prediction?

This is a fairly general question: I have typically found that using multiple different models outperforms one model when trying to predict a time series out of sample. Are there any good papers ...