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

learn more… | top users | synonyms

1
vote
1answer
41 views

Determining whether time series is Gaussian from autocorrelations

Can one say anything about the "Gaussiness" of a time series merely by looking at its autocorrelations? I find this hard to reconcile. Let us say I find that there are significant autocorrelations in ...
0
votes
0answers
16 views

evaluate the similarity between two time series

I have two time series, $\mathcal{T}_1$ and $\mathcal{T}_2$, each time series is of two dimensional. One time series is collected from two sensors (SA, SB), and the other is collected from other ...
0
votes
1answer
66 views

Neural Network - Classification from Time series

I'm a .Net programmer who is fairly new to neural networks, but I know some of the concepts. I have connected .Net to my copy of Mathematica 10 This is a classification Our business problem is ...
0
votes
1answer
84 views

Time series forecasting using Support Vector Machines

I have been trying to use Support Vector Machine method for time series forecasting. I have seen allot of research papers, but nobody shared the code or tool they have used for that. Got some ...
1
vote
1answer
35 views

How to determine if the mean of 1 time series is significantly greater than that of a group of other time series?

I have 20 different time series data over the past 60 days. Each time series is collected from 20 different geographic zones. A test was run in zone A but not in the remaining 19 zones. Is there a ...
2
votes
1answer
79 views

Kalman filter with control inputs in python?

i am trying to fit a simple kalman filter with input controls (in this case step input) in python. i am using filterpy (http://filterpy.readthedocs.org/). my code is: ...
0
votes
0answers
8 views

Relation between CV and remainder component in stl()

I'm using stl decomposition and I red that the size of grey bar indicates the variation compared to the variation in the data. But, when I tried this in R I didn't get the same thing. Here is an ...
0
votes
1answer
54 views

Allowing for resets in an accumulating time series

I am extracting data from IP21 (a sensor historian logging system). This is a weightometer weighing material moving over a conveyer belt I need to calculate hourly differences/increases from an ...
0
votes
0answers
24 views

How to forecat a ARMAX model with 1 step ahead forecast in R?

I have divided my time series to 2 parts and I have used first part Y1TS[1:n2] for model fitting and Y1TS[n2:n1] for forecasting ...
0
votes
0answers
25 views

Forecasting Sales with Multiple Regression

I want to forecasting week sales by using Multiple Regression. Since I have factors that influences weekly sales. I know when we use commercials, reduce the price, which placements in the stores, ...
1
vote
0answers
25 views

Imputing missing gaps in irregular time series

I am currently working with time series data that was sampled at irregular time intervals. There are some gaps of missing data, i.e. a bunch of subsequent observations are missing every now and then. ...
0
votes
0answers
67 views

Problems fitting a repeated measures model (time series analysis): fixed-effect model matrix is rank deficient so dropping 1 column / coefficient

I’m trying to fit a model with 4 parameters by not including all the interactions, just including the interaction which got biological sense. This is my data ...
1
vote
1answer
42 views

Which one to compromise between MAPE and Adj R square in multiple regression

I'm trying to forecast sales of a product based on the other variables like Competitor sales, Fuel Price and CPI (Consumer Price Index). The below given output (based on 1 to 44 months) gives me the ...
2
votes
2answers
43 views

The importance of stationary time series

I am a bit confused with stationary time series. Data transformations (detrending, difference etc) are used to seek stationary time series so that we can treat correlation as a constant over time. ...
0
votes
0answers
25 views

Predicting binary outcome for multivariate time series in R

I have some monitoring dataset for 90 patients. It consists of about 10 parameters (continuous variables) that were recorded each 1 minute 3-4 days for every patient. I know the binary outcome for ...
0
votes
0answers
25 views

Binary outcome prediction based on multivariate time series in R

everyone! I have some monitoring dataset for 90 patients. It consists of about 10 parameters (continuous variables) that were recorded each 1 minute 3-4 days for every patient. I know the binary ...
0
votes
0answers
39 views

Can you perform bootstrap resampling from a sampling distribution?

The quick and to-the-point question I have is: Can you perform bootstrap resampling on a sampling distribution, using the sampling distribution as if it were an original sample of observations? What ...
1
vote
0answers
18 views

How to model ringing effects?

There's a discussion here about modeling birthdays: http://andrewgelman.com/2013/12/19/happy-birthday/ You'll see that there's a big dip in births on Christmas, and there are a lot of births just ...
0
votes
0answers
30 views

Comparison between ARIMA and ETS models

I have a time series that I'm fitting models to, using R. I have chosen an ARIMA model based on minimising the AIC_C values. The ETS model (ets()) was chosen based on minimising the model accuracy ...
0
votes
1answer
83 views

Algorithms for Time Series Anomaly Detection

I'm currently using Twitter's AnomalyDetection in R: https://github.com/twitter/AnomalyDetection. This algorithm provides time series anomaly detection for data with seasonality. Question: are there ...
0
votes
0answers
81 views

How to estimate Error Correction Model in Eviews?

I am using time series data of six metal prices (in real terms) to estimate its trend over the last 55 years. for that i am using a modified quadratic model which integrates an error correction term. ...
1
vote
1answer
33 views

Does the recurrent neural network require the length of input samples all the same

Theoretically, the training of RNN doesn't require that the samples must have the same time length, but it seems to me that some software or open-source requires that the input data has the same time ...
3
votes
2answers
166 views

Which econometric indices are best for macroeconomic variables?

I want to test index models that are applicable to macroeconomic data to test my hypothesis in R or some other statistical software (I have most of them). The properties of most of the macroeconomic ...
3
votes
0answers
51 views

How to determine rise time of a signal from its noisy background timeseries?

I have temperature vs. time data from a thermometer. The data was recorded using a DAQ system, has a stable background level, and some random noise. At a certain time, the temperature begins to rise ...
4
votes
3answers
103 views

What is the straightest line I can make using a linear combination of time series

I have 3 processes which generate an output in the form of a time series. I want to choose a linear combination of the processes that will result in the straightest line possible (I think this ...
1
vote
2answers
64 views

Stationarity of Detrended and Deseasoned time series

I removed trends and seasons from given time series and plotted the residual time series. I would like to know if there is any way that this plot could suggest that residual series is stationary? What ...
0
votes
1answer
31 views

Deterministic trend and noise

I have a chicken-egg problem in time series: How do we remove the deterministic trend in time series when you have a guess that the noise is non-normal? How do we check if the noise is non-normal ...
0
votes
1answer
39 views

Calculation of VaR of a time series using a GARCH(1,1) ARMA(1,1) model

Please, I've been stuck all the weekend in this problem, does someone know how find the Value at Risk 10 days ahead (for example) using a GARCH(1,1) ARMA(1,1) Model. Thank you very much Rodrigo *If ...
1
vote
0answers
52 views

Automatic periodicity detection in noisy multi-variate time series data

What techniques can i use for automatic periodicity detection specifically in noisy "multi-variate" time series data? By multi-variate time series, i mean that i have multiple (>1000) variables ...
2
votes
1answer
77 views

markov chain with probability trends

I have clients with debts that can pass from states own 1 bill, own 2 bills, own 3 bills, leave the service, new debtors and owe nothing. So I could calculate the probabilities of being in state ...
0
votes
0answers
5 views

Time points density

I have a date-time points and I want to visualize the density of them in time. How can I calculate the density of this time points for example in a 1 minute or 1 hour intervals or what ever. Thanks
1
vote
0answers
35 views

Interpretation of autocorrelation plots using ccf in R

I'm not that familiar with time-series type data. I am looking for some advice on the interpretation of the following plots of autocorrelation between two variables. I used ...
1
vote
0answers
29 views

Time Series Stationarity and Histograms

In a paper I am reading, the author discusses stationarity and plots the histogram of returns for the time series he is studying. I was wondering if there was any relationship between stationarity of ...
0
votes
0answers
65 views

Interpreting Correlogram

I am wondering if anyone has any ideas as to how to interpret the following correlogram? Or in general, what is the best way to treat/interpret a correlogram that exhibits a curve
1
vote
1answer
60 views

Time-series and autocorrelation inequality

I am having problems proving for a weakly stationary process $\{X_t : t\in T\}$: $\rho_X(2)\geq 2 (\rho_X(1))^2-1$ where $\rho_X(j)=corr(X_t, X_{t+j})$. So far I have shown that $-1\leq ...
1
vote
1answer
53 views

Linear regression vs Time series analysis

I am confused that when I should use static model (like cross-sectional regression) or other forms of time series model. I see some examples of analyzing time ordered data by crosss-sectional ...
0
votes
0answers
39 views

analysis of bank account record

I am new to the field of time series analysis, but I would like to have a look at my bank account and determine my spending habits. I read a lot about clustering of multiple time series but I think I ...
0
votes
0answers
35 views

Classification of time series with SVM

Background: I'm currently trying to find interesting anomalous interferences in time series data. I have quite large database of collected data with many different measurements (over 2k measurements ...
0
votes
1answer
14 views

Which method is suitable when the independent variables are of process steps over time and the dependent is binary?

I'm quite confused with some methods I've read about - growth models, repeated measures, time-series fixed effects models etc. I'm trying to understand which method is most suitable to the data I ...
3
votes
0answers
57 views

ARMA models and invertibility

I'm reading the book Time Series Models by Franses et al. It says that if we have an $ARMA(1,1)$ model with $\phi=1$ and $\theta=-1$ we have $y_t=\epsilon_t$. So, this means that in the equation ...
1
vote
2answers
80 views

Does possible non-stationarity matter if the model is OLS?

I am working on an assignment where the current model is an OLS model that models the percent change in a variable, X, by regressing it against a bunch of economic variables such as unemployment rate, ...
1
vote
0answers
13 views

Method needed: parameters leading up to an event

I apologize, this is probably a simple question. I have 3 or 4 time series variables (temperature, depth, etc.) and I have the times that a specific event occurred (about 100 different events of the ...
1
vote
1answer
68 views

How do you generate correlated ARMA(1,1) models?

I am interested in generating two ARMA(1,1) time series with a pre-defined cross-correlation p between x(t) and y(t). If you could please provide the mathematical framework and the code in R for ...
0
votes
0answers
17 views

How to predict values? [duplicate]

I have a simple time series with at least a measurement a day. I would like to know if there are algorithms that can deal with missing values and measurements that are not taken always at the same ...
0
votes
0answers
15 views

Discrepancy between hierarchical top level time series and direct sums - using package hts

I have an xls file with sales data from 12 shops, each selling two types of goods. If I read in the xls file and sum up sales for each month (ignoring the two types of goods and just looking at the ...
0
votes
0answers
48 views

Any machine Learning models to predict dates?

I have a general question regarding machine learning models. The idea is to predict what DATE the customer is likely to make transactions or purchases. Variables present in the data set are item, ...
0
votes
0answers
14 views

Why do orthogonal complements come into play in the Granger representation?

Consider the Granger representation of a VAR model. (See : here). Can anyone explain me how in this representation Equation 1, page 4 the orthogonal complements of $\alpha$ and $\beta$ come into ...
1
vote
0answers
29 views

Is autocorrelation also a problem with data collected from different respondents?

I have a question regarding autocorrelation in multiple linear regression. I analyse data on IPOs over 6 years. I look at a dataset of 450 companies which have listed their stock at the stock ...
3
votes
1answer
58 views

How do you simulate two correlated AR(p) time series?

I would be interested in the mathematical framework plus code in R if possible. Basically I want to find out the parameters of the two AR(p) models if I already specificed a certain cross-correlation ...
1
vote
1answer
29 views

How to apply cross-validation for time series analysis using a regression-based approach?

I'd like to know how to use cross-validation for time series analysis using a regression-based approach without incurring in under- or over-fitting. In particular, assume we have an input time series ...