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

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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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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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27 views

How can i predict data just for specific days in R? [on hold]

I would like to know how to estimate data in specific period of time in R. for example, in my problem i should estimate data from 26th October 2005 to 31st October 2005 in monitoring station and I ...
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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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16 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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1answer
53 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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26 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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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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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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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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1answer
11 views

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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15 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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18 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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51 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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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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14 views

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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1answer
23 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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19 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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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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49 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
29 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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2answers
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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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1answer
38 views

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
40 views

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 ...
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20 views

Getting an error message “Error in if(reached.threshold < min.reached.threshold)…” while training network using neuralnet package

I'm using R to create train and test a neural network on a time series (the annual sales of a company over a large period of time). As using the package's default learning algorithm (resilient ...
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1answer
35 views

Dealing with nonstationarity and autocorrelation

Relationship between interest rates and retail sales. I have a time series sample of quarterly data for 10 years. My dependent variable is retail prices and independent variables are interest rates, ...
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23 views

Sampling Distribution of Sample Correlation Coefficient

For a linear process $X_t=\mu+\sum_j\varphi_jW_{t-j}$ where $W_t$ is white noise and $\mathbb E(W_t^4)<\infty$ , $$ \begin{pmatrix} \hat\rho(1) \\ \hat\rho(2) \\ \vdots \\ ...
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Hodrick-Prescott Filter, Time Series, SDE, and Ito Isometry

The background of this question is a paper written by Morten O.Ravn and Harald Uhlig, titled "On Adjusting The Hodrick-Prescott Filter For The Frequency of Observations" Consider the decomposition of ...
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29 views

R: Time series forecasting alternatives to ARIMA [on hold]

I was using WEKA to perform time series forecasting based on lagged variables and machine learning algorithms: Time Series Analysis and Forecasting with Weka I am trying now to do something similar ...
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Forecasting with Dynamic values using R [migrated]

I have a Json object : {"tcDetails":[{"project_nm":"abc","id":"1","n_tc":"32","TC": [{"29/06/2015":50,"30/06/2015":45,.....}] {"level":[{80,85,90,95}]}]} ...
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Eviews and Forecasting Linear Regression with AR(1) Error Term

This question is geared towards those who are familiar with Eviews and forecasting with linear regression in the case of AR(1) error terms. Consider the classical linear regression model where the ...
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EWMA or Moving Average when Estimating Trend in Seasonal Data

What is generally the best practice when estimating trend (non-seasonal component) in seasonal data? Centred Moving Average as suggested by MatLab docs Averaged EWMA (backwards & forwards) as ...
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Making a Time-series Stationary: Order of Operations

Following various sources including this post, which is the correct approach to making a time-series stationary? Remove trend Remove seasonality or Remove seasonality with estimated trend ...
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Comparing Variance Ratio tests to Hurst exponents

I have used the Chow Denning test and the Hurst exponent (Peng, Whittle and R/S methods) to examine if a particular time series follows a random walk. My results are conflicting between the 2 tests. ...
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21 views

Which is the best way to check (with some certainty) if the mean of a time series is a constant?

I am testing the time series output by a light sensor, and trying to know when dawn and dusk end. I used a cusum test to check when light level starts changing, and now I need to know when it ...
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32 views

Choosing the right forecasting method [on hold]

I have 27 years monthly price data of a commodity. I want to forecast the price for the next six months. How do I choose the right forecasting technique? The data has both trend and seasonality. I ...
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1answer
13 views

Comparison of time series models

I'm trying to create a model for a series $X = \{X_1, X_2, ...\}$. I don't assume that the $X_i$ are identical distributed nor that they are independent but at least that they have something in common ...
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why nsdiffs() returns this time series is not seasonal while it looks seasonal?

nsdiffs() returns this data is not seasonal and hence no seasonal differencing is required. nsdiffs(TrainTs, m=frequency(TrainTs), test=c("ocsb","ch"), max.D=8) Error in nsdiffs(TrainTs, m ...
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10 views

Time series data plotting and reduction with maintaining significant changes [closed]

I have time series data with second resolution for 5 years so its huge data for plotting. I have to plot graph for month and year wise as well. Now plotting each year how to reduce the dataset so ...
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Stationarity of time series data

The following are plots of the original data first order difference values of original data and the first order difference of the log transformed data. Can someone please tell me which of 2 and 3 ...
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43 views

Exactly The Same Autocovariance Function of Two Time Series

A MA(2) process : $$X_t=W_t+\frac{5}{2}W_{t-1}-\frac{3}{2}W_{t-2}$$ where $\{W_t\}\sim WN(0,1)$ And another MA(2) process : $$X_t=W_t-\frac{1}{6}W_{t-1}-\frac{1}{6}W_{t-2}$$ where $\{W_t\}\sim ...
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1answer
29 views

Why does randomising the order of measurements remove time as a confounding variable?

Say we're interested in the difference in x between Group1 and Group2. We might measure 50 samples from Group1 then 50 samples from Group2. If the accuracy or precision of our measurements change over ...
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5 views

Problem with TSO function in tsoutliers [migrated]

I am trying to get the tso() function of the tsoutliers package to work but I keep running into the same maddening error when the dplyr package is loaded that I can't seem to figure out. Any ideas? ...