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

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Detecting varying time rates

I was thinking about detecting the veracity of user ratings by examining the time-stamp. Basically I have a series of times $(t_1, t_2, \ldots, t_n)$. So assuming that ratings should normally come in ...
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1answer
808 views

Johansen test loading matrix

I'm using the URCA package in R to test for cointegration by Johansen's method. Can anyone tell me what the weights (loading ...
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4k views

Performance evaluation of auto.arima in R and UCM on one dataset

I started evaluating and comparing some methods in forecasting. I used Price of dozen eggs in US, 1900–1993, in constant dollars in the R software FMA package. I held out the last 10 years for ...
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832 views

Expert forecasting software evaluation

I have question on evaluating forecasting software with expert systems: Are there any objective assessment (not from the manufacturer) on expert forecasting software in the literature? I found two ...
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3k views

AR(1) coefficient is correlation?

Is the ar1 coefficient from an AR(1) model the "first order correlation of the noise" of a time series? I'm using R's aws package and one of the arguments of the ...
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326 views

Features selection by filter methods for multivariate time series

I have a data set in which the samples are multivariate (about 30 variable/features) time series. These samples refer to two classes. I would like to select the variables more relevant to discriminate ...
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484 views

Simulation vs analytic methods to forecast time series process

Just asking if someone knows why the prediction intervals are quite different when one uses a time series analytic method of estimation versus when one simulates such time series. For example, I ...
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563 views

degrees of freedom in ARIMA model

I estimated parameters of an ARIMA model by arima function in R and I calculeted t ratios or t statistics for each parameter. Now I want to find p values for t test, what is my degree of freedom? is ...
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136 views

Averaging Correlations

I am working with patient experience data where patients answer questions regarding their stay at the hospital. Each question is then given a correlation value as it relates to the final "overall ...
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747 views

Time series forecast by Principal Component Analysis

Suppose that I have a series of $M$ time-observations of $N$ "quantities" $z_1(t_1),...,z_1(t_M)$, ..., $z_N(t_1),...,z_N(t_M)$. I want to estimate the values of $z_1(t_{M+1}),...,z_N(t_{M+1})$. This ...
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286 views

Detecting statistically significant clustering of continuous values

I'm working with biological sequence data where each position in the sequence has an associated continuous value. I'm ignoring the sequence content so the data is very similar to a time series with ...
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392 views

How to get the values ​​of the probability density of a given data using R? The goal is to get the values of the function not the graph [closed]

The problem is the following: If I have data from 2002 to 2005 of operational risk then I want to get the value of density associated with this. ...
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1answer
368 views

What is the reasoning behind defining the MA process in terms of unobserved errors?

Why is the MA(1) process phrased as $X_t = \epsilon_t + \theta\epsilon_{t-1}$, with the $\epsilon_t$ defined as the (unobserved) errors between model fit $\hat X_t$ and observed $X_t$? Why is the MA ...
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110 views

Online learning to maximize profit

I have a software which takes input as investment and gives the output as return on a particular stock. Now profit metric $x_i$ is defined as the ratio of return $g_i$ to maximum possible return ...
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597 views

AR(1) process with heteroscedastic measurement errors

1. The problem I have some measurements of a variable $y_t$, where $t=1,2,..,n$, for which I have a distribution $f_{y_t}(y_t)$ obtained via MCMC, which for simplicity I'll assume is a gaussian of ...
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52 views

Using sequential observations to perform online prediction

I'm trying to perform predictions from a sequence of events. My problem is this: Data collection: Suppose you can continuously observe a person sitting in a library. You take note of every time that ...
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213 views

Measure for temporal “spread”

I basically have a timespan from January until August (or any other timespan) which is divided into active periods (denoted by a red line in the plot) and inactive periods (the rest). What I want to ...
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2k views

Bootstrapping residuals: Am I doing it right?

First of all: From what I understood, bootstrapping residuals works as follows: Fit model to data Calculate the residuals Resample the residuals and add them to 1. Fit model to new dataset from 3. ...
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1k views

Volume of the 95% confidence ellipsoid

I'm dealing with 3D data that are the trajectory of a point over time. I would like to have an indication of how much it is "spread" in space and I thought about using the volume of the 95% confidence ...
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517 views

ZScore threshold and low values time-series

Example of z-score computation: 1 - E.g. Time-series: [0, 0, 0, 0, 1] Current: 1 Mean: 0.2 Std: 0.44721 Z = (1 - 0.2) / 0.44721 ~= 1.7888 2 - E.g. ...
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1k views

Is chi-squared the right method to compare time periods?

We manufacture foobars. In July, 91% of foobars were defect-free, but in August that figure was 89%. Would chi-squared be the right method to determine if the difference of 2% between July and August ...
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973 views

How to cluster time series?

I have a question about cluster analysis. There are 3000 companies, which have to be clustered according to their power usage over 5 years. Each company has values for every hour during 5 years. I ...
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382 views

Using simpler models in place of more generalized and complex models

I was reading about BATS (Box-Cox transformation, ARMA errors, Trend and Seasonality) and TBATS (Trigonometric, Box-Cox transformation, ARMA errors, Trend and Seasonality) models. I was wondering ...
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189 views

Comparing employee sales monthly data despite regional differences

I'm not exactly sure how to title this thread, or what tags to use since advanced statistics isn't really my thing right now. Please change the title and tags as needed to improve this question. Say ...
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2k views

How do difference-in-difference designs account for temporal autocorrelation

Although there are doubtless many techniques for studying the impact of a discrete intervention over time, I am interested in two which have achieved widespread adoption in the social sciences: ...
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195 views

Confused with basic time series terminology

I am a bit confused with the basic time series terminology: Consider the following words: fitted values forecasted values in-sample forecasts out-of-sample forecasts in-sample fit I am using ...
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294 views

Forecasting with large, high frequency dataset

I am doing my master's thesis and I must compare various forecasting techniques at different frequencies of datasets. I am using my universities dataset, the REDD dataset, UCI dataset and CER Ireland ...
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147 views

One time series tends toward the (linear) function of another time series, how to find that function?

I have two time series $p_t$, the daily market price of a particular kind of good $f_t$, the daily production of such good Now assume that there is a unique relationship that tells you the optimal ...
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433 views

Removing a 'trend in variance' from a time series

I'm looking at a time series which has a very strong daily cycle in it. However, on top of having a daily cycle in the actual values of the time series, it also has a very strong daily variance cycle. ...
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1answer
108 views

Predict near future data from another correlated data source that varies quicker

I'm trying to figure out a way to predict the evolution of some data in the near future by using another data source that is correlated to that one but that varies quicker. For instance, I have the ...
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113 views

What does “X”stand for in “XARMAX”?

What does "X" stand for in "XARMAX"? I searched online but couldn't find it. Is there "XARMA"? Thanks!
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1answer
118 views

Frequency on Tbats function in R

I have 3 complete years + 4 weeks of weekly time series data, of which one of the years is a leap year. To calculate its frequency should I do (365x2+366)/(3*7)? Thanks!
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4k views

Definition of autocorrelation time (for effective sample size)

I've found two definitions in the literature for the autocorrelation time of a weakly stationary time series: $$ \tau_a = 1+2\sum_{k=1}^\infty \rho_k \quad \text{versus} \quad \tau_b = ...
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82 views

How to approach prediction of new observations with incomplete data from model built from complete data

I currently have a gradient boosting model that uses the gbm package in R that classifies observations at the end of a year. Daily behaviors are logged for each ...
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50 views

Why can't I use the variance of the sample average in the Central Limit Theorem for the weak-stationary process?

Under mild conditions $\dfrac{\bar{X}-\mu}{\sqrt{\sigma^2/n}}$ approaches the standard normal (where $\sigma^2$ is the process variance, not the marginal variance $\sigma^2_x$). Why is the ...
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404 views

Regression model of large, correlated, heavy-tailed data

I have a large panel-like data set: about 15,000 individuals, on average 350 time points, two dozen variables (plus some more variables we left out for context-specific reasons). What I want to ...
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1answer
410 views

Poor forecast results of a state space model

My aim is to compare the forecast performance of several time series models. I have a bivariate dataset, and applied three different models to it: 1) A univariate Arima model (applied to the first ...
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476 views

How to estimate a model with fixed and random effects for a long panel dataset?

NOTE: I am using Stata for doing this. I have a long panel dataset, meaning my N is much smaller than my T. I have N = 5, T = 61. I tried to estimate my model, but I get an error related to the ...
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182 views

Shrinkage Estimator for Newey-West Covariance Matrix

This is a cross post. I would like to apply the Newey-West covariance estimator for portfolio optmization. Up to lag one it is given by $$ \Sigma = \Sigma(0) + \frac12 \left (\Sigma(1) + \Sigma(1)^T ...
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1answer
12k views

How to run a Granger Causality Test with Stata

I'm doing a study on the determinants of FDI (Foreign Direct Investment) in the ASEAN countries. Before doing a panel data analysis, I'd like to run a Granger Causality Test between the potential FDI ...
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71 views

Testing for a root larger than 1 in AR(p)

My question is the following: How to test for a root larger than 1 in AR(p) process from its observations. Thanks in advance.
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1answer
446 views

Time-series classification - very poor results

I am working on a time series classification problem where the input is time series voice usage data (in seconds) for the first 21 days of a cell phone account. The corresponding target variable is ...
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183 views

What test to use for qPCR time course data with multiple genes and multiple strains?

My knowledge is severely lacking when it comes to statistics.. I have qPCR data at different times after induction and I don't know what kind of statistics to use on it. I have values for 9 genes at ...
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1answer
177 views

Automatic detection of level changes in series of prices

I have a large number of time series which consist of pricing data of consumer goods. As expected the prices show trend and seasonality. However my main problem is to detect large level changes in the ...
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987 views

Why does auto.arima() give negative output?

This is the dataset on which I am working currently, which is production data. Data: ...
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709 views

How to calculate p-value for Cross-Correlation for two time series with delay?

I have two stationery time series that I want to see are they correlated or not. I decided to work with cross correlation, there is a good answer in Correlation between two time series but I dont know ...
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1k views

When testing CAPM why is r-squared so low?

I am testing CAPM, Fama-French & Carhart-models (so a 1-factor, 3-factor and 4-factor model) for financial portfolios (60 observations). There is one type of portfolio with low R²'s. The CAPM ...
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568 views

What is the implication of unit root of MA?

A ARMA(p,q) process is weakly stationary, iff the root of its AR part is not on the unit circle. So its weak stationarity doesn't depend on its MA part. But what can the positions of the roots of its ...
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1answer
9k views

How to correctly fill in missing values in panel data?

So, I have panel data that look like this: The data that are missing, is because we were not able to find full data in the annual reports of the banks listed in the dataset. There is no real ...
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35 views

Comparing components within a single time-series (physiologic data)

I have physiological data (electodermal activity) from several subjects recorded continuously during a task with multiple components. I'm interested in comparing whether the response within each ...