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

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Outlier treatment in Vector Autoregression (VAR) Model

Data: Multivariate Time Series, Series 1) Demand of a product 2) Rainfall data both available at monthly level from 2010-2013. Approach: I am trying to estimate the effect of rainfall on demand of ...
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295 views

Filtering techniques and noise

Suppose we have some house price data for 30 years (1970-1999). This is yearly data (30 data points). Suppose some major event $X$ happened on 1980. I want to see whether this event affected prices ...
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11 views

What quantifies a stable parameter?

I'm optimizing 5 parameters for an option pricing model. Now I want to asses whether these parameters are stable over time (i.e., a year). For this I create about 12 subsamples and estimate the ...
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12 views

statistical comparison of power spectrums over all frequencies

So I have N=147 control time-series signals and N=134 treatment (THC) signals. I want to compare if there are any significant differences in frequency power in the two groups. The top part of the ...
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165 views

LIBSVM parameter search in time series

I try to predict values for regression in LIBSVM. My data is in time series. I use gridregression.m file in LIBSVM to find optimal parameters c, g and p. Gridregression.m file use cross validation to ...
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227 views

Independent t-tests and Technical Indicators: Voodoo, Axes, and Objectivity

First off, I'm not trying to crowd source a personal printing press (i.e., not doing this: "I'm using strategies $x$, $y$, $z$ in the stock market and..."). Instead, I'm looking for feedback on ...
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10 views

arima function in R, data= and subset= not available? How to specify training set?

I would like to fit my arima model on some subset of my full data, say, based on observations within a certain time range. Normally, say in fitting an lm() object, I would use the subset= argument ...
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31 views

Time Series Forecasting Method to use both Predicted and Predictor variables

I am learning Predictive modeling and building a Forecasting model to predict Insurance sales in US as a part of my academic project. I want to do Time Series forecasting. I have Y(t) as my response ...
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15 views

How is the prediction variance defined?

I wonder how the output $var.pred returned by ar.ols() in R is defined? It is not the variance of a prediction value, is it? I ...
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19 views

Piecewise nonlinear regression by MLE in R software

I have been working with nonlinear models whose parameters have been estimated by Maximum Likelihood. Also, I use the "Vuong" test for model selection in non-nested models, this test requires to have ...
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22 views

Which type neural networks for time series classification

I would like to use neural networks to classification of time series ( I have some Patterns and I want to adjust input time series to an appropriate class) -ist it possible to do this job with ...
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176 views
+50

Standard deviation of several measurements with uncertainties

I have two 2 hours of GPS data with a sampling rate of 1 Hz (7200 measurements). The data are given in the form $(X, X_\sigma, Y, Y_\sigma, Z, Z_\sigma)$, where $N_\sigma$ is the measurement ...
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16 views

analysing difference in variability between multiple related time series

I have constant time series (yearly from 1950 to 2010) of the abundance of several species that were captured by different groups. These series are somewhat related because the quantity of all species ...
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70 views

How to produce the minimum forecast error using R?

Considering that we want to use optimize() on the interval [0,1] how can I write an R code for finding the value of β that produces the minimum forecast error without using external packages like ...
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28 views

what is the return value of predict in the fGarch package

I have a question about a quit sophisticated model for a time series. Suppose $ \{X_t:0\le t\le T\}$ is a time series. The plot of autocorrelation function and partialcorrelation function suggest and ...
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6 views

testing for heteroskedasticity with Breusch Pagan in time series

I want to use a Breusch-Pagan test with time series data, I have regressed the residual on the independent variables and added a lag for the dependent variable: is this the right way to be going ...
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1answer
49 views

ARIMAX model's exogenous components?

Does anyone know, considering an ARIMAX model that fitting a stationary process Y, then does the exogenous components for the model need to (weakly) stationary? I think exogenous components can be ...
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7 views

Methods for analysing effects of percentage mortality on population data with zero/low abundances

I want to analyse the effects of percentage mortality from two sources (a predator and a disease) on the population abundance of a host measured at 12 sites for 8 years, with the main aim being to ...
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12 views

Measure of intermittency/continuousness of a signal

I have three signals (below) each having the same standard deviation, however, are clearly very different temporally. Is there some such metric that could be calculated for each of these signals to ...
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77 views

Understanding factor potentials in PyMC

I'm trying to understand factor potentials from the PyMC documentation, but need some help on the implementation piece--or it may turn out that I am misunderstanding how potentials work altogether. ...
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1answer
152 views

How to fit a simple count time series INAR(1) model in R

I am trying to perform a simple time series analysis with count time series data. My data is a sequence of small integer values like 0,1,2 and 3. I learned from various sources that INAR model would ...
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32 views

Multivariant time series in R. How to find lagged correlation and build model for forecasting

I'm new in the page and pretty new in statistics and R. I'm working on a project for college with the objective of finding the correlation between rain and water flow level in rivers. Once the ...
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7 views

Trend estimation for participation?

I have logs for users and posts in a blog platform for 3 years. I can easily find out how many posts each user have made per day/month/year/etc. What I want to find out is if the frequency of posts ...
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51 views

Using non-stationary time series data in OLS regression

I am using 1983-2008 annual data to test if both gini coefficients and gross national saving in China and the US can affect the US current account balance. The data seem to be non-stationary, but I am ...
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6 views

Ljung Box test for a muivaraite time series?

From Tsay's Financial Time Series, Ljung Box test for a time series is for a multivariate time series is ... I wonder how to see the test statistic for a muivaraite time series is a ...
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1answer
31 views

How to interpret the expression of MA(1) as AR($\infty$)

When AR(1) is expressed as MA($\infty$), I can interpret it as: let's say my wage this year depends only on last year's wage and a random shock (my boss' mood). But last year's wage also depends on ...
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138 views

Moving average ARIMA error term

Lets say that I have a time series data $Y_{t}$. I'm trying to forecast using am moving average MA(1) model using Box Jenkins methodology. The following is the equation for an MA(1) obtained from a ...
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66 views

Dealing with dependant data when estimating probability of an event happening

I have 10 years worth of data from 1970 to 1980 (40 quarters). For each quarter I have five measurements M1, M2, M3, M4 and M5. TWIST: Although the data I have is on individual patient level, the ...
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8 views

Appropriate Test? Is there a “t-test” for ratios when large number of data points and multiple runs?

N.B. I only have a very basic statistics background since I am in grade 9 in high school. Any help would be GREATLY appreciated. My Experiment: -Part 1: 2 variables (A and B) were each sampled in my ...
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1answer
148 views

Using anomalies to calculate trends of seasonal data

I commonly see people doing trend analysis of (monthly) timeseries data which show a strong inter-annual cycle following this scheme: compute climatological means ("mean January", "mean February", ...
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3 views

Plotting the overlay using an exponential smoothing of a time-series using `lines()` [migrated]

I have the following code so far but I am not sure which function I should use for plotting the yearly average measurements of temperature for New Hampshire, from 1912 to 1971, and overlay an ...
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170 views

time series with different length: feature extraction and classification [on hold]

I have a binary classification problem, where each data point is multi-channel time-series, which can be represented as a matrix $T \times F$, where $T$ is the time-series length, and $F$ as the ...
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14 views

Times series and starting point incidence

I'd like to modelize the height of a plant which depends on Its aging (in months). The month it has been planted. For instance a plant of 3 months is higher if it has been planted in march than ...
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690 views

Assessing peaks in time series of cell signal data

I am measuring for the existence of response in cell signal measurements. What I did was first apply a smoothing algorithm (Hanning) to the time series of data, then detect peaks. What I get is this: ...
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17 views

Unexpected error from running predict variance after mgarch dcc

I am getting an unexpected error from running predict variance after mgarch dcc command. I am using Stata 13 for Windows. I tried to find the dynamic correlation between two time series by using ...
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1answer
124 views

Forecasting the target variable vs building a causal model and forecasting causal variables

I want to know the approaches people use to forecast lets say unemployment rate .... By itself it might not fit a time series model (ARMA) very well as the trend is dependent on many external factors. ...
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1answer
102 views

Determining odd time series

I have a number of time series which are derived of same underlying data. However, the data in each comes from a different source, so they may be slightly lagged or differently enriched but ...
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17 views

Plotting a comet like animation for multiple variables

I am trying to code a visualization with 4 variables ( Carbon emission, Energy consumption, population and year) The data set i have collected so far looks like this With C1990 representing Carbon ...
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1answer
119 views

Fit VAR model with unknown order in Matlab

I have a multivariate observed time series $Y_t$ and I want to find the best fitting VAR process for it. I have the econometric toolbox in Matlab and can use 'vgxvarx' if I pre-specify an order for ...
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1answer
237 views

ARIMA vs ARMA on the differenced series

In R (2.15.2) I fitted once an ARIMA(3,1,3) on a time series and once an ARMA(3,3) on the once differenced timeseries. The fitted parameters differ, which I attributed to the fitting method in ARIMA. ...
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46 views

Building a time series model using more than independent variables

I am working on a project, and I am totally new to statistics. I have sales data for last two years at week level, along with other variables like temperature, holiday (TRUE/FALSE), where holiday are ...
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37 views

Is there any tool that can do Vector ARIMA modeling in time series

Vector ARIMA model is used in multiple time series analysis. I am just wondering if there is any software or tool can be used to build the model. Some tools,like R, can only be used to predict the ...
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22 views

Fitting a best fit line to this time series

I have the following hourly time series data and would like to fit a best fit line to it: There seems to be a periodicity on a daily basis and a weekly basis. By this, I mean there are patterns ...
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1answer
98 views

Time-varying Coefficients

I have time series data on fish catches from 1950-2011. I wish to implement a regression model with varying coefficients. I'm aware that cox models etc. exist and implementation via the ...
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195 views

Error correction model (to test for asymmetry) with stationary I(0) variables

I have price series which are all stationary without taking any difference --> I(0). Can I still perform an ECM model to test for asymmetry? For example: Y= constant X; taking the residuals and ...
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3answers
179 views

How to combine time-series based features with different frequencies

I have 3 features which I want to use in my classifier. They are all time-series data-based. However, they are all at different frequencies and there have different matrix dimensions. I was wondering ...
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46 views

Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...
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25 views

Impact of lagged values on identity variable

Let's say I'm working with the following simplified macroeconomic accounting identity Y_t = C_t + I_t + G_t, meaning that GNP in time ...
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7 views

Time series classification pointers

I'm new to ML/statistical learning and would like a few pointers in what I need to study to solve my problem. (FTR, I've done an Intro to AI course, classifying Fisher's Iris dataset and things like ...
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36 views

Using results of regression on raw observation values to approximate results of regression on relative change between observations (Simple, Linear)

this is my first time on Stack Exchange so if I did something wrong please tell me. I have a time series dataset. There is an observation $(y,x)$ for each continuous time $t$. Let’s say for each day ...