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

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Variance of annual return based on variance of monthly return

I'm trying to understand the whole variance/std error thing of a time series of financial returns, and I think I'm stuck. I have a series of monthly stock return data (let's call it $X$), which has ...
2
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1answer
237 views

How to define sample space for discrete random variable

If $S$ is the sample space of some discrete random variable $X$, what is usually given as its superset? $S \subset \mathbb{R}$ or $S \in \mathbb{Q}$? The $X$'s I have are digitized biomedical data. ...
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161 views

How to compare the accuracy of predictive algorithms when the predicted value contains measurement error

I am conducting (somewhat casual) research on the accuracy of several algorithms meant to compute a value when given a set of experimentally gathered variables, including time. The issue is, the true ...
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1answer
599 views

Fourier phase randomization

Can anybody please explain or point to an online resource that explains the Fourier phase randomization technique? I encountered it in the context of comparing the cross-correlation of two signals ...
2
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1answer
47 views

Correlation based on one object

Background: I have two random variables - height and weight. We often estimate correlation between them based on random sample of individuals. However, what would happen if I took only one individual ...
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91 views

Sensible Transformations of Economic Indices like CFNAI and ADSBCI in Time Series Analysis

I am trying to fit an unobserved components model for revenue and transactions for a firm where I also use some exogenous variables that capture economic conditions. The UCM decomposes a time series ...
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100 views

Test Markov Chain properties of time series

First of all, please excuse if I don't use the proper terminology for this problem. I have a markov chain composed by two states: When in state 1 the output is drawn from an exponential ...
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1answer
329 views

How do I estimate the $e_t$ from a moving average model?

I have an ARIMA(0,2,1) model. How do i estimate the $\hat{e}_t$ component of the model. I have read a whole lot of theories that confuses me the more. Is there any ...
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114 views

Time series properties

Has anyone any idea how one could distinguish time series according to certain properties? The only time series properties I know are stationarity/nonstationarity and ...
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3answers
538 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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255 views

Lagged term in time series with stationary errors: too good to be true?

I often have datasets where there are many animals, in several treatment groups, and each animal's body weight is measured at regular intervals over the course of its lifetime. The response of body ...
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1answer
498 views

How to tell if the relationship between time series variables changes over time?

Lets start out by saying that I'm a novice with statistics. I'm looking to analyze the relationship between Return on Sales (ROS) and Asset Turnover (TAT) over time to see how they impact firm ...
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2answers
5k views

Does it make sense to use a date variable in a regression?

I'm not used to using variables in the date format in R. I'm just wondering if it is possible to add a date variable as an explanatory variable in a linear regression model. If it's possible, how can ...
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391 views

How to conduct an event study?

Could you please tell me how to conduct an event study? I have 60 companies and 16 events. I am computing the abnormal return within 20 days around the event study (-10,10). Should I do it for ...
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0answers
107 views

Choosing distance function in kernel regression forecasting?

Is there a method to find the right distance function in non-parametric regression? I use some time series to learn forecasting. Series are nonlinear and non-gaussian. I can get the right dimension ...
0
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1answer
134 views

Scaling a normal distribution while using EWMA

I have a time series of daily data and am assuming each point in the time series is normally distributed. If I have a distribution of the daily data and want to scale this to cover a month (30 days) I ...
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2answers
73 views

When should you consider using time series in analysis?

I have a number of projects that I am working on where data is collected over time periods of months to years. My first question is when should time be considered as a factor in conducting analyses ...
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157 views

Detecting trends in a data stream in real-time

I'm trying to detect trending topics on Twitter in real-time. What I'm doing is every time I get a tweet I assign the tweet to the cluster that talks about the same topic as the tweet. Regardless of ...
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2answers
714 views

Call volume: time series regression model from 52 weeks a year and lagged predictors

I have been adamantly searching the web to learn how to successfully implement a dynamic regression time series in the forecast package for R. The time series data that I am using is weekly data ...
4
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1answer
884 views

How to find patterns and identify changes in them in time series with R

This is my first question on stats, just trying to learn the basics of time series analysis with R. So any good suggestions about learning resources will be highly ...
3
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1answer
214 views

Methods for time-series prediction depending on multiple parameters

We have hourly time-series data of the status of a system: number of people present at different train stations. We collected it for a year, and we want to use it to train a model to predict the ...
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1answer
80 views

What is the difference between a one-sided filter and a two-sided filter when looking at time series analysis?

I'm looking to understand the difference between the two and grasp in which situations each might be preferred over the other.
3
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1answer
80 views

Interpreting Regression Results: Combined Data Points

I'm new to statistics, so I'm having some trouble interpreting some results. Let's say I was interested in creating a daily wind speed profile for the arctic during a 30 day period. I have 5 ...
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618 views

Preparing data and understanding auto.arima outputs, in R.

I am trying to fit an ARIMA model with one exogenous variable using in R the function auto.arima with xreg option. I am having ...
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2answers
205 views

Removing outliers and calculating a “lowest” attainable price from a pre-determined/fixed time series of prices

Just a foreword, I'm not a mathematician or otherwise statistically skilled. I know my way around calculating standard deviations, but it's all self taught. I'm a programmer with limited stats ...
4
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1answer
2k views

Difference Between Simultaneous Equation Model and Structural Equation Model

Can anybody please help me to understand what are the differences between Simultaneous Equation Model and Structural Equation Model (SEM)? It will be great if somebody can provide me some literature ...
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37 views

How to compute multiple date ranges for wildlife occurrences

Say we are trying to predict occurrences of lightning bugs based only on the dates on which people reported seeing them. So climate change, weather, and other influencing factors are imaginary. So ...
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1answer
307 views

How to model multivariate time series

I have a set of $n=1000$ samples of 4 dimensions (multivariate) where each measurement obtained from GPS tracking data is taken at a time interval representing spatial coordinates $(x,y)$, velocity. ...
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437 views

Nonlinear regression: heteroskedasticity and correlated residuals

I'm performing regression analysis of some data. I believe I have to use a non-linear model with the form $y = at^b + c$ where $t$ is time. A log transform won't linearize the data here because of the ...
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165 views

Two questions on indexing and regression

Is it OK to have causals indexed on different base years? Amongst many references, I think the answer is “no”. Is that true? p.360 Wooldridge [Introductory Econometrics: A Modern Approach, 5th ed]. ...
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1answer
5k views

Forecasting Function R (Holt-Winters HW approach)

I was trying to forecast using the "hw" method in R. I have data which follows: ...
3
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1answer
202 views

Clustering of count data

I am currently trying to find clusters in a data set that looks like this: ...
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24 views

Technique for neurovascular experimental analysis?

I'm trying to run statistical analyses on the data I got from some neuroscientific experiments. Because I don't have a solid math background, I would really appreciate any input as to what tools to ...
3
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118 views

Determining stability in a time series via probabilistic modeling

I recently started to read Probabilistic Programming and Bayesian Methods for Hackers and really got interested in the topic and PyMC. I especially like the example of the first chapter where ...
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359 views

Outlier detection of an unevenly spaced time series

I found the Rob H answer to this question very interesting and works pretty well. However, I also would like to apply this methodology to an unevenly spaced time series like the following: ...
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96 views

What form of analysis should be used for loss given default estimates?

I am working on BASEL II IRB models and we have to estimate loss based on historic defaults. There are different outcomes/scenarios we have identified that a default can encounter that will affect ...
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1answer
447 views

How to map a trajectory to a vector?

I have a series of data points in this form (timestamp, lat, long) for a set of users. Each user has a trajectory when he travels from point A to point B. There might be any number of points from A to ...
3
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2answers
602 views

How to identify spikes in a noisy time series?

I have time-series data of brain cell spiking. It's basically got a baseline of random noise with large spikes interspersed. I want to be able to algorithmically cluster the spike portions of the ...
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287 views

Are running mean plots good indicators for time series convergence?

I want to know whether a time series has converged. I looked around the MCMC literature (which requires doing something similar -- knowing whether a chain has converged) and found the following: ...
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1answer
107 views

Confused about independence and prediction power of data

What is the correct way (if there is one) to think about when authors claim that stocks have produced some percentage annual return X over every 20 year period of time? They might calculate this by ...
2
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2answers
1k views

Seasonal dummies significance issues

I have a question concerning the significance of the seasonal dummies in my ARIMA-model (I do not use seasonal differencing or seasonal AR/MA as I have quite regular seasonality and I get better ...
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3answers
130 views

Forecasting of density function

I am doing some research about forecasting time series of probability density functions. We are aiming to forecast a PDF given historically observed (usually, estimated) PDF. The forecasting method we ...
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1answer
168 views

How to improve forecasting accuracy?

I got some users' history data and generated some sequences of real numbers. The length of each sequence is between 15 and 25. What's more, I do not know whether these sequences have patterns and the ...
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1answer
148 views

Period effects in pooled time series data in R

This is closely related to a question I asked yesterday but I've now got a much more complete answer on which I was hoping to get feedback. The previous question was just looking for conceptual advice ...
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78 views

Comparing different step functions

I measured the appearance of certain events over time in different conditions and I would like to know whether there is a difference between the happening of these events. I thought of plotting the ...
2
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1answer
2k views

Pooled time series regression in R

I've got data on mail volume sent by household for seven age groups, with 12 years of data for each age group. I originally ran a simple regression on each age group individually and realized I needed ...
2
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1answer
824 views

How to check adequacy of a time series model using residual autocorrelations?

This was in an past exam question I came across. A first-order autoregressive model has been fitted to a time series of 50 observations giving $\hat\mu = 15$ and $\hat\alpha =0.6$. The first 12 ...
4
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1answer
1k views

How do I interpret the figure output from package dlnm in R?

I am performing distributed non-linear lag models in R. I got the figure result of dlnm as shown in the vignette (pdf) on page 13: The X-axis is lag, which I ...
3
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1answer
419 views

Residuals in double seasonal exponential smoothing

I have a time series with muliple seasonal cycles, which are 24 and 168 hours for my case. I would like to use Double Seasonal Exponential Smoothing method to forecast, which was published by James W. ...
3
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1answer
3k views

Connection of t-statistic and p-value in augmented Dickey-Fuller test

My project is about purchasing power parity (PPP). I am checking whether the real exchange rate of Canadian dollar(CAD)/US dollar(USD), Japanese Yen(JPY)/USD and Great Britain Pound(GBP)/USD has a ...