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

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101 views

Confusion about the term “stochastic drift”

After reading lots of material about the subject, I believe that the term "stochastic drift" is defined in a two different ways. These two different definitions make the term unambiguous and I assume ...
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1answer
97 views

Testing “trends over time” of dummy variables

Let us say this is an output of a model I ran in Stata, where int_retis a continuous variable and time1-...
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1answer
50 views

Is this multivariate normal? 2 time series linked by a common process

Summary: Consider a scenario where you observe the inputs ($X$) to and outputs ($Y$) from a process ($B$). If I have a model describing how $X$ evolves over time, and a similar model for $Y$, how do I ...
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34 views

On the Fly Time Series modeling

I'm dealing with a system which monitors and records a time series (half hourly) which I plan to use to build a double seasonal time model (if possible using something that already exists, such as ...
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30 views

repeated measure ANOVA with non-consecutive repeats

I have a somewhat of a repeated measure setup but wanted to check if repeated measure 1-way anova can be applied here (assuming underlying assumptions of normality, sphericity etc are met). ...
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29 views

Feature selection for support vector regression with time series as features

I would like to select features for a support vector regression for forecasting. I would like to forecast a value at point t with the values t-1,...t-x as features. Now I want to select the most ...
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2answers
125 views

What is the best way to proof your time series has a deterministic linear trend

In case you suspect your time series has a linear trend, what is the best way to prove it? If you just regress it against time, you ignore the auto correlation of the time series so I assume that is a ...
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2answers
99 views

step by step tutorial for newbie

I'm looking to join the field of statistics and more exactly to forecasting. I'm a software developer and I just started playing with R. Can you recommend me some tutorials related to forecasting, ...
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73 views

What is the frequency of a time series for hourly data?

I am using R for time-series analysis and predictions, the package 'forecast' to be more precise. I am in a dilemma. I have hourly data that needs a prediction and needs to be analysed. I am using the ...
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3answers
255 views

Performing a time series ARIMA model on natural gas power demand using the forecast package from R

I've been attempting to forecast natural gas power demand and how it is affected by temperature and price. I'm not sure if I have done everything correctly (relatively new to R), but I do seem to get ...
2
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0answers
47 views

Calculate the variance and the 1st order autocorrelation

The stochastic difference equation is $$ {{y}_{t+1}}=\frac{1}{a}{{y}_{t}}-\frac{b}{a}{{x}_{t}}+{{\varsigma }_{t+1}} $$ where $ {a}>1; $ $ {{x}_{t}}=(1-\rho )\overline{x}+\rho ...
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41 views

Best data series to teach time series econometrics?

I will be teaching a short course on time-series econometrics to third-year undergraduates. It will be part theoretical, part applied (students using econometrics software). I am looking for great ...
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1answer
58 views

ARMA conditional density

Consider the ARMA(1,1) process \begin{align} y_t=a_1y_{t-1}+b_1\epsilon_{t-1}+\epsilon_t, \end{align} and assume $\epsilon_t$~$N(\mu_t,\sigma_t)$. And $\mu_t$ and $\sigma_t$ are all known. ...
4
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1answer
70 views

Sample mean of random walk

I would like to find out if the sample mean $T^{-1}\sum\limits_{t=1}^T{y_t}$ of the simple random walk $y_t=y_{t-1}+u_t$ with $u_t \sim i.i.d$ $N(0,1)$ diverges or converges? I am looking for a ...
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0answers
24 views

Modelling a time series with the “optimal” combination of N proxy series

I have a time series T. I also a universe U of time series such that A, B, C ... Q are time series that belong to the universe U. My problem decomposes into the following sub tasks: Find a subset ...
0
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1answer
62 views

test for comparing means of two time series [duplicate]

I wonder if there is a test for comparing means of two different time series (both measured at the same person or two different persons)? Would be very glad if someone can help me!
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1answer
74 views

Which is better, stl or decompose?

I am doing time series analysis using R. I have to decompose my data into trend, seasonal and random component. I have weekly data for 3 years. I have found two functions in R -- ...
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0answers
17 views

Simple asymmetric ARCH vs asymmetric ARCH

I am working with GARCH models. As I try to familiarize myself with Stata's options I have run into a number of questions I am having problems answering. What is the difference between SAARCH and ...
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1answer
80 views

Fitting a time-varying coefficient DLM

I want to fit a DLM with time-varying coefficients, i.e. an extension to the usual linear regression, $y_t = \theta_1 + \theta_2x_2$. I have a predictor ($x_2$) and a response variable ($y_t$), ...
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3answers
93 views

Can nonstationarity be told from the autocorrelation function?

Here "stationarity" means the first and second moments don't change over time. From a page of Time Series: Theory and Methods, by Peter J. Brockwell, Richard A. Davis In this chapter we shall ...
3
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1answer
74 views

Predicting a continuous outcome using point process descriptors

I have measured a series of times for discrete events along with a continuous variable. So essentially I measure a point process $P: t_1, t_2, \dots, t_n$ and values $A_1(t=x_1), A_2(t=x_2), \dots, ...
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1answer
45 views

Detecting 'causality' in Likert-time series data

[Note] I've decided to re-write my question for the sake of brevity. The original question can be found below. Suppose a number of individuals fill in a questionnaire at a multiple number of time ...
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32 views

Multiple time series methods for trend identification, forecasting etc

I have several time series consisting of aggregated macro-economic indices and I am trying to choose one or several appropriate techniques in order to answer a number of questions. First, I need to ...
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1answer
81 views

Can we apply multiple regression on time series data?

It always create a doubt to me, whether we can apply linear or non linear multiple regression on time series data. If yes, should I consider year also an independent variable. Thanks, Arushi
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42 views

Gather insights from quarterly financial forecast data

I am trying to analyze a quite large (~25,000 rows) dataset of financial forecasts. The forecasts are usually not derived from algorithms, but come from a large number of analysts who forecast the ...
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1answer
35 views

Fitting a reduced-form MA(3) time series model in R

I am trying to fit an ARIMA model for a certain financial time series. I've used EViews for modeling, and have decided to fit a so-called reduced-form MA(3) model, where only the third lag is ...
2
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1answer
75 views

One-way ANOVA appropriate?

I am assessing the performance of a hospital ward over 6 years. There have been two sets of changes to the ward over this time: after year 2 and after year 4. I have collected data in 4 sample ...
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2answers
146 views

How to test for presence of trend in time series?

Apart from detecting trend from a time series plot, how do you test for its presence before removing the trend using moving average? I fitted a mathematical trend to the data and the slope was ...
0
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1answer
61 views

Having difficulty forecasting a tslm model

I'm having issues forecasting a model of the following form. y1 <- tslm(data_ts~ season+t+I(t^2)+I(t^3)+0) It fits my data very well, but I run into a problem ...
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27 views

Meaning of 'Data Adaptive' and 'Non Data Adaptive' time series representations

I was reading a paper and came across a tree-figure which split time series representations into "Data Adaptive" and "Non Data Adaptive" representations. In the Data Adaptive branch were ...
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53 views

What statistics to use for testing hypothesis about regression coefficient when n is greater than 30

What statistics to use for testing hypothesis about regression coefficient when n is 120. I plan using a z score but am not sure.
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2answers
100 views

How to determine the correlation between 2 time series while controlling for a 3rd?

I would like to determine the relationship between two variables after controlling for a third. Specifically, I want to know if the prices of mercury and gold over time are correlated with each other ...
0
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1answer
98 views

How to simulate only stationary AR(1) with φ = 0.9?

I am interesting in simulating AR(1) processes with 0.9 parameter and n = 10. The itterations should be 10000. When I was trying to run the program it gave me an error in the estimation procedure. ...
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2answers
94 views

Is this a valid application for a Kalman filter?

I have 2 time series; Both the series are tracking inflation.(they have different sampling frequencies) Blue is the official CPI released by the US government. Red is an independent group's measure ...
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55 views

What are the stationarity requirements of using regression with ARIMA errors for inference?

What are the stationarity requirements of using regression with ARIMA errors (dynamic regression) for inference? Specifically, I have a non-stationary continuous outcome variable $y$, a ...
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135 views

Eviews vs R (Statistical Software)

Are there many features in Eviews that R misses? I have heard that especially when dealing with time series R is less extensive than Eviews. Is this true? Which of the two packages contains most ...
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0answers
47 views

Distribution fitting (maximum likelihood) for autocorrelated data

I have some time series data that shows autocorrelation and seasonality. I want to fit a distribution to it. To use maximum likelihood it needs to be uncorrelated. I first fit a GARCH and an ARIMA ...
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25 views

How to test if the mean of data collected over many days is significantly higher on a predicted day

I have some data examining blog posts on different days. Basically, about 2000 news articles pertaining a certain topic were sampled and each blog post was given a positivity percentage score ...
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2answers
157 views

Ordinal/continuous vs dummy variable for time series regression/data mining

Let's suppose I have a time series data that I would like to regress $y$ on $x$ and $Time$. See below for the dataset. ...
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1answer
68 views

Principles of Time Series Clustering

I would like to understand complexity of time series clustering. Clustering is similarity based, so as a basic step we evaluate distance between to points in a multidimensional space. In time series, ...
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1answer
37 views

Estimating the asymptotic distribution of a quasi maximum likelihood estimator

We consider the following GARCH(1, 1) model: $y_t = h_t \epsilon_t$ where $(\epsilon_t)_{t \in \{1, \dots, n\}}$ are i.i.d. random variables with mean 0 and standard deviation 1. $h_t = \omega + ...
2
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37 views

What time-series model to use for mostly linear, but limited values?

I'm interested in fitting a model to several types of time series that all behave similarly: Depth of a work queue Disk space available Idle CPU time available None of these values can go below ...
5
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1answer
70 views

Modelling slopes over time

I have data of the price of a product before a newer version came out and after a newer version came out. I'd like to model the slope of the product pre the new product, and post the new product. ...
2
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26 views

Is it okay to take the average of several normalized time series?

I have 3 time series (10 years) of economic data for 3 countries. For another analysis that I am doing, I should try and reduce these into preferably 1 time series. For this analysis I don't care so ...
3
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1answer
67 views

Simultaneity of price in sales modeling

The price of a product has signficant impact on the total sales. Hence modeling sales would give the incentive to include price as a regressor (amongst other variables). Suppose we would estimate this ...
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0answers
31 views

Estimator of autocovariance in a wide-sense stationary process

From Wikipedia http://en.wikipedia.org/wiki/Ergodic_process One can discuss the ergodicity of various properties of a stochastic process. For example, a wide-sense stationary process $x(t)$ has ...
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4answers
72 views

Time series analysis for 2 series where one is dependent on another

If I have two time series $A$ and $B$. $A$ is dependent on $B$. I want to forecast future values of $B$. What statistical techniques should I learn and try? As an example consider a time series of ...
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0answers
45 views

How do you check ergodicity of a stochastic processes from its sample path(s)?

How do you check ergodicity of a wide-sense stationary stochastic processes from its sample path(s)? Can we check ergodicity from a single sample path? Or do we need multiple sample paths? One ...
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20 views

Comparing shape of time series data whist ignoring scale

I have a number of sets of time series data. Specifically each set of time series is associated with a single study subject. Each series measures the area between the vocal chords over a breath period ...
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2answers
162 views

What are good ways of plotting distributions over time using R?

I have ~400 individuals and >10k timepoints each (simulation results) I would like to be able to monitor as they change over the course of time. Plotting all individuals is too messy, plotting mean ...