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

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time series forecast problem

i have a resaerch in forecasting population size in my country by using exponential smoothing method, my data was for six years, for several states, i used spss program and used time series analysis, ...
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Interpretation of coefficients in linear regression: first difference of logs

what is the correct interpretation of coefficients in time series regression when using first differencing on logs of the DV and in certain IVs. FD(lnY)=c+beta1*ln(X)+beta2*FD(lnZ) The log ...
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Strictly Stationary Time Series with Infinite Moments

Can someone give me an example of a strictly stationary time series with infinite moments? I am reading a book on Time Series by Wayne A. Fuller where it is said that a strictly stationary time series ...
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Recommended Study Area For Processes

I am looking for a machine learning area that deals in processes for logistics. If anyone can show me some use cases or even point me in the direction of a couple of algorthims. Im currently using R ...
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2answers
14 views

What are some good (and fast) alternatives to dynamic time warping?

I am planning to cluster tens of thousands of time series of different lengths into two groups.
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9 views

ARMA-GARCH model selection / fit evaluation

I'm trying to fit an ARMA-GARCH model to a data set of FTSE 100 log returns. However, I'm not able to find a well-fitting model. Below are the ACF and PACF of the log return series and the ACF of the ...
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13 views

Properly calculate mean and SE for meta-analysis

I want to perform a meta-analysis, for which I have data from 30 different experiments, each of them with two different treatments. I have three different types experiments based on how the data are ...
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1answer
17 views

How do I measure the significance of a trend [on hold]

I have a 5 year dataset by month, so I have 69 discrete measures of the same value. That value shows an increasing trend, but I'm unsure how to measure it's significance. My team would also like a p ...
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39 views

What does the following ACF curve mean ? (Picture attached)

I was checking for seasonality and other dependencies and this is the curve I get . There's no apparent seasonality....but what exctly does the falling slope mean? Any help would be appreciated. ...
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15 views

Cointegration in R - Standard error, test statistic and p-value of weights

I'm using urca package in R version 3.2.1. I used ca.jo function on a set of I(1) regular time series variables - taking two at ...
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1answer
22 views

Correlation coefficients of a time series

I have 100 simulations of an ARMA(1,2) process, created with R is such a way: ...
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16 views

Time-series cross-sectional classification problem

I have a time-series cross-sectional dataset consisting of 100 individuals that each had 4 features measured yearly for 21 consecutive years. One of the features is binary and the other three are ...
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141 views

Statistical test for increasing incidence of a rare event

I have following simulated data of 2500 persons regarding the incidence of a rare disease over 20 years ...
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26 views

Poisson vs. Gaussian in Geomagnetic Data

I've been studying geomagnetic signals using a threshold approach to detect pulse events in the data. The question here is what is the significance of the crossover of stddev and mean as the ...
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838 views

Why does the variance of the Random walk increase?

The random walk that is defined as $Y_{t} = Y_{t-1} + e_t$, where $e_t$ is white noise. Denotes that the current position is the sum of the previous position + an unpredicted term. You can prove that ...
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13 views

Coherence vs. Magnitude Squared Coherence

Currently I am writing my master thesis. The theory part is about the turbulent wind field generation, where the coherence (not magnitude squared) is used: $$\text{coh}(f) = ...
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10 views

Mixed effects model for repeated measures to test for factors that are either constant or dynamic within an individual over time

I am dealing with a rather complicated dataset with repeated measures of the same individuals at various time points (samples were collected at different time points and different number of samples ...
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1answer
22 views

Simulation of time series with R [on hold]

I'm new on time series. I'm trying to solve an exercise on the simulation of an ARMA process. The problem is the following: Generate 100 simulations, each with n=60 elements of an ARMA(1,2) process ...
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6 views

Package ‘JPSurv’ - Trends in incidence rates [on hold]

Has anyone ever used the JPSurv package in R to look at trends in incidence rates? The original software put out by the NIH - Joinpoint - is not compatible with my computer (a macintosh) and so I ...
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34 views

How to test whether a random walk have a upward or downward trend

I have applied Kalman Filtering Method to get the estimates for time-varying coefficients (using DLM package in R). The model is like $S_{t} = \alpha_t * A_t + \beta_t * W_t + \gamma_t * A_t * W_t + ...
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33 views

non-invertible weakly stationary AR processes

ok, so I know (for example) that $X_t = 2X_{t-1} + e_t$ for iid $e_t$ is stationary. But how do I go about proving the condition $Cov(X_r, X_s) = Cov(X_{r+t}, X_{s+t})$ for all integer $r, s, t$ ...
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2answers
19 views

Detrending a series that moves about zero

How can I avoid my de-trending model from blowing up? Do I need an additive model rather than a multiplicative model? If so, is there anything I would consequently need to take into account? Can I ...
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0answers
8 views

Can I run an SVM on sparse temporal data without a regular time interval?

I have data of occurrences with timestamps that could be days or months apart. I'd like to enter the values natively as follows. Are there any SVM algorithms that can support such an input? day 1: ...
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Help¡ How do I solve this problem time series? Subject: Geophysical time series [on hold]

A problem of interest in the analysis of geophysical time series, involves a simple model for observed data containing a signal and a reflected version of the signal with unknown amplification ...
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17 views

Evaluating correlation of 2 time series

I did some research on this website and I found a few questions about correlation between 2 time series. However, all of them end-up with cross-correlation as answer, which is not really what I want. ...
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Vector Autoregressive Model: residual's kurtosis proportional to number of lags?

I have some transformed data set (windspeeds that are nearly-weibull-distributed). I transformed this data which results in near-normal distribution (close to no excess kurtosis and skewness of zero). ...
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23 views

How to choose which test to use to determine if a time series is non stationary?

I want to determine if my time series is non stationary. I looked many articles and have learned there is not just one formula - ADF. It seems you must use some series of tests and assumptions. But I ...
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77 views

How can I recreate a Weibull distribution given mean and standard deviation and the shape and scale parameters are unknown?

Figure 2 is a Weibull distribution of three different wind farms in Canada. These 3 probability distributions were combined in a study to obtain a common wind speed model. I will be using this common ...
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1answer
28 views

How to detect variable seasonality pattern

We have predicted and actual (daily) data for past 3 years. We use 90 days of data for prediction. Generally our predictions are very accurate, but we receive unusual traffic for few days/weeks ( like ...
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1answer
67 views

Identification of navigation pattern (lapping, pacing, random and direct) from X,Y co-ordinate in known physical layout

I have X, Y and Z co-ordinate of the movement patterns of a person for 30 days over some known physical layout. This is unevenly spaced time-series data with maximum frequency of 2Hz while in motion. ...
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11 views

Difference between clipped time series, PRBS, PN sequence and their application in signal processing

A real valued time series can be converted into binary series through the process of clipping. Clipping, or hard limiting, a time series is transforming a real valued time series Y into a binary ...
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14 views

What techniques infer dependencies between time series?

I'm working on an ML project. We have an app where users can track 1) binary variables and 2) quantities over time on a scale from one to ten. For example, at a given time they may track whether they ...
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Prerequisites for time series and ARIMA

I am working on forecasting sales for 2016. The details of the problem is: 2014 - sales happened only between Jan-Apr 2015 - Sales happened only between Jan-Apr The sales in rest 8 months of the ...
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How do I perform a Wald Test with multivariate Granger Causality Analysis

I am doing a Granger Causality Analysis for three economic variables (GDP, CO2 emissions and Total Energy Consumption) of Puerto Rico. I am using a Toda-Yamamoto Procedure implemented in R R. I am ...
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16 views

What does the sigma^2 figure mean when fitting a model to a time series in R?

I have a time series in R, and I am using the arima function to fit it to a SARIMA model. I would like to use the parameters it returns to write the time series equation by hand, but in order to do ...
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21 views

What is the best way to extract time-series shared by two variables?

I have one dependent and several independent variables. I want to extract the time-series of the independent variable that is shared with the dependent variable. In other words, I want to extract only ...
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2answers
66 views

Analyze trend given a set of points

Suppose I have a set of N values representing EUR/USD rate... [ 1.10 , 1.20 , 1.25, 1.20, 1.19 ] Which is the simplest way for analyzing if values tend to raise or tend to fall? I'm looking for a ...
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Correlation computing time series data of unequal sample size

I am working on a computing a correlation between two variables X and Y. Both are time series and were recorded during the same period. 6/25/15. However X was recorded much more often than Y. ...
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12 views

Which time series model to use?

Hi I have a large data set of objects, each containing a list of the same attributes. The data is arranged in a time series so that the value for an attribute for an object is indexed by its time. ...
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Covariance of ARMA (2,1)

I am preparing for an exam and need help. Consider the following estimated ARMA(2,1) model, y(t) = 0,05 + 0,83y(t-1) + 0,13y(t-2)- 0,15e(t-1) + e(t): Given the unconditional variance and 1st order ...
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24 views

Time series analysis with known outliers

Let's say I have a time series of site usage data that I would like to analyze. The data is for people visiting my site, with a known seasonality that I can easily calculate, but in addition, there ...
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Touch times to authenticate user

for a project I gathered touch data of different users when they tap a rhythm repeatedly on the touch screen in a game. ...
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20 views

Transfer function of pure ARMA time series model

Is it theoretically justifiable to calculate/use the transfer function of a pure ARMA model? I would like to be able to use the transfer function representation to put the state equations into their ...
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6 views

X11 deseasoning: too few datapoint for S3x3 moving average?

Do I have too few data points to use a $S_{3\times3}$ moving average? I have the following dataset for January months, ...
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52 views

Marketing Data with many zeros

I am working on a marketing data which is a time series data with marketing spend done through different channels and revenue generated. The data looks like this : My data contains too many zeros ...
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Deciding the lag while testing for timeseries data stationarity

I am currently reading up on time series forecasting using ARIMA in SAS. I just began to go through what has been explained here : ...
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1answer
30 views

Do we need to detrend when do Cross-Correlation between two time series?

I have a group of time series variables and I want to found out the relationship among them. The method I use is to calculate pair-wise correlation between two time series and found out those with ...
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AR(2) model is causal

AR(2) model is : $$X_t=\phi_1X_{t-1}+\phi_2X_{t-2}+W_t$$ Where $W_t\sim N(o,\sigma^2)$ I want to prove AR(2) model is causal . So , I tried as : $$X_t-\phi_1X_{t-1}-\phi_2X_{t-2}=W_t$$ ...
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Modeling Time-Series with a lower bound

I am trying to fit a model to a time series that has a lower bound (at around -150). Using an ARIMA model, running simulations often leads to the time series hitting (and going underneath) this lower ...
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2answers
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Linear correlation between two sets of data

I have various data sets that correspond to values (in percentage) at given time points (hours, up to 10 hours). The total number of data sets of values at given time points is 8. My question is ...