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

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104 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
0
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1answer
10 views

Consistency of OLS in presence of deterministic trend

For consistency of OLS estimator for linear model $$ y_i = \beta^T x_i + \epsilon_i, \; i = 1,\cdots, n, $$ the model assumptions are usually (the ones I am familiar with) The sequence of random ...
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2answers
40 views

Time series - correlation and lag time

I am studying the correlation between a set of input variables and a response variable, price. These are all in time series. 1) Is it necessary that I smooth out the curve where the input variable is ...
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9 views

What types of statistical analysis technique available to compare two different time series

I am currently looking for suggestion to compare or study the two different period time series like sales in 2000 and 2001
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1answer
19 views

Comparing polynomials

I've got a bunch of data on pop singers' performance on the Hot 100 charts over time, and I'm trying to compare the early part of different artists' careers. For example, I might look compare Miley ...
0
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1answer
34 views

Why we check the residuals of ARIMA model for white Gaussian?

I have problem about the assumptions and model verification of ARIMA models. I know that Gaussian distributed assumption is not necessary for fitting ARIMA models but I wonder why a lot of people ...
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17 views

Identify the stationary time series

Identify the stationary time series for which $$ \gamma(h) =(-1)^{|h|}+\cos \left(\frac{\pi}{4}h\right)$$ is ACVF. This is a homework problem. Stuck at first level. Please give some hints. Thanks in ...
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1answer
7 views

Holt-Winters and Abnormal termination in LNSRCH

I try to fit data with Holt-Winters function in R. Nevertheless, i am getting the following message: ...
2
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3answers
782 views

Does applying ARMA-GARCH require stationarity?

I am going to use the ARMA-GARCH model for financial time series and was wondering whether the series should be stationary before applying the said model. I know to apply ARMA model the series should ...
0
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1answer
70 views

Error Calculating MVN Likelihood of Time Series with AR(1) Errors in R

I'm having trouble calculating the likelihood of a time series with AR(1) errors. I am generating my covariance matrix according to page 2 of (http://cran.r-project.org/doc/contri...regression.pdf), ...
2
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1answer
31 views

how to calculate a summary value and statistical error in time series

I have a set of data that comes for empirical measurements over a number of days. From the beginning of the experiment to the end of it, every five minutes temperature was measured inside (Ti) and ...
3
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1answer
68 views

Time series forecasts of appointments with pre-registration

Looking for some tips and ideas. I get a list every day of the number of appointments for each day for the next two weeks for a clinic. I have quite good history of these list, and the actual number ...
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0answers
16 views

breakpoint analyses on multiple series: how to detect common points

I have 20 time series that span the same period (100 days each), from 4 species sampled at 5 different location. I made a loop to perform a breakpoint analysis on all of them, resulting in 0 to 3 ...
0
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1answer
13 views

How to blend multiple time series models?

I have three different linear, multi-variate time series models with a best fit against the same observed value $Y$ at 1 minute, 3 minutes and 10 minutes horizons respectively. Each model is using ...
0
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1answer
20 views

Hodrick-Prescott derivation in lay terms

I am currently working with the Hodrick-Prescott filter. I would like to understand the equation in lay terms.
3
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1answer
25 views

Spread-Level Plot versus Power Transformation Functions in R

I'm having trouble interpreting the results from the Spread-Level Plot function in R (car package). The documentation says: PowerTransformation spread-stabilizing power transformation, ...
2
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1answer
362 views

How to apply an AR(MA) model to a prewhitened signal?

I have two (vehicle velocity) signals that should consist of similar "latent" drivers, but have different autocorrelation structures. The driver-signals are quite nasty statistically, so I'm not ...
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0answers
9 views

How to down weight correlations in my microarray analysis?

Background: I have been tasked in one part of my analysis to reproduce a method used in another study as follows in bullet points form: Microarray data from a number of time points Calculate ...
0
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1answer
69 views

How can i find the significance of the cointegrating coefficients in output cajorls-function in R?

I investigate the long-term relationship of some variables but in the output provided by cajorls-function, I can't see for each coefficient if it is significant? This is provided by the ...
2
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1answer
273 views

Forecasting optimization techniques in fantasy baseball

I am currently trying to build a better forecasting model for my fantasy baseball roster. I currently am using commonly accepted projected season statistics (ZiPS from Fangraphs) to determine the ...
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1answer
18 views

Cosinor analysis with repeated cycles

I'm interested in developing a model for the circadian rhythm of hormone levels via a cosinor analysis. I just started looking into cosinor analyses so I have a few questions. The data is being ...
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0answers
10 views

Autoregressive model with input variables in proc arima procedure

I am currently working on the time series analysis for series Y but I have to use other two variable A and B as an input variable in SAS proc arima procedure. But I am unable to interpret the cross ...
0
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1answer
15 views

How do I combine multiple time series models to create a generalizable predictive model?

I have several time series that are each observations of the same phenomenon, for example: Observation 1: 10, 25, 36, 72, 80, .... Observation 2: 32, 46, 78, 90, 100, .... Observation 3: ...
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1answer
34 views

How to normalize time series?

This is a general question on normalization of data so that all the variables are within the same range. Why do we normalize data in pattern classification? How to normalize time series which is ...
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1answer
161 views

Trying to use Holt-Winters to fit this data

I'm trying to fit the data in this message (daily temperatures) using the Holt–Winters technique in R, but can't get the seasonal example in here to work. Is this not possible with these data, or am I ...
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0answers
54 views

How to test Simultaneity

I am researching the influence of ΔENVIRONMENTAL TAXES+ΔENV.EXPENDITURE =>ΔCO2 EMISSIONS. and further, the influence of ΔCO2 EMISSIONS =>ΔENV.TAXES after a certain period of time. I have a time series ...
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1answer
14 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
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1k views

Data has two trends; how to extract independent trendlines?

I have a set of data that is not ordered in any particular way but when plotted clearly has two distinct trends. A simple linear regression would not really be adequate here because of the clear ...
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1answer
208 views

How to plot spectra of an AR(2) process

I am stuggling with this problem and was hoping to find some guidance to answer it. Let $y_t=\phi_1y_{t-1}+\phi_2y_{t-2}+\epsilon_t$, with $\epsilon_t\sim N(0,1)$. Now, I want to plot the spectra ...
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1answer
30 views

How to stationarize profit and loss data with an increasing variance and large negative values for time series analysis?

PnL can take large negative values, and its variance increases over time as the firm grows. If we do differencing, an increasing variance remains. If we take log, negative values cannot be defined. ...
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2answers
170 views

Consequences of modeling a non-stationary process using ARMA?

I understand we should use ARIMA for modelling a non-stationary time series. Also, everything I read says ARMA should only be used for stationary time series. What I'm trying to understand is, what ...
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0answers
10 views

Timeseries analysis for increase of database memory usage over time [on hold]

Hi I have data that shows memory used/increased over time in terms of GBs. Now I have data something like shown below: Db1,25gb Db2,50gb And so on I have few ...
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3 views

R-package dlm (dynamic regression, dlmRegMod), especially CAPMDLM example… please help me! [migrated]

I am a graduate student in Business. Fortunately, I found a DLMCAPM code (https://github.com/VSRonin/DLMCAPM/blob/master/Final%20Work.R) for a bivariate case in GitHub regarding on the Dynamic ...
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5answers
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Why use vector error correction model?

I am confused about the Vector Error Correction Model (VECM). Technical background: VECM offers a possibility to apply Vector Autoregressive Model (VAR) to integrated multivariate time series. In the ...
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16 views

How to perform multilevel interaction

I have 400 observations = 100 individual * 4 years. Which equation is correct? $$x_{1} + x_{2} + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ $$x_{1} + x_{2} + \left(x_{1}2013\right) + ...
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4answers
211 views

Most effective way to learn time series with poor quant background

End goal will be practical application (model building) by using time series analysis to analyze/forecast macroeconomic/finance data. Background: I have taken stats, introductory econometrics, ...
7
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1answer
171 views

Evaluating Time Series Prediction Performance

I have a Dynamic Naive Bayes Model trained on a couple of temporal variables. The output of the model is the prediction of P(Event) @ t+1, estimated at each ...
5
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1answer
69 views

When forecasting sequential data is it best to use auto-regressive models or build a more traditional n x p dataset with features?

I'm familiar with the use of auto-regressive models when it comes to forecasting a single vector of time-series data. Is anybody familiar with a more traditional modeling approach, i.e. - creating ...
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0answers
10 views

estimating period and dealing with Non negative values in forecasting

When I read time series in a ts object and put a period: 1) tr <- ts(data[,4],frequency=). This works for two different periods and decomposes perfectly to show (downward) trend, seasonality and ...
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1answer
83 views

How to sum correlations, or, calculate correlation of disjointed variables

I'm trying to calculate the correlation of two variables, but the array is disjointed in the middle - but I'm trying to obtain one correlation coefficient. See the excel file I uploaded. Because ...
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2answers
508 views

Rolling analysis with out-of sample

I have a model that looks like lm(y ~ lag(x, -1) + lag(z, -1)) So basically, this is a time series regression with exogenous variables, and I want to carry out ...
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2answers
99 views

Standard deviation of percentage changes in a time course

I ran into a problem analysing some data I produced. I measured concentrations in biological samples in a time course manner. I measured three replicates for each of the seven time points. I can ...
2
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3answers
69 views

Forecasting: Different Model for 1 month, 2 month, 6 month forecasts?

I'm still trying to expand my statistics and forecasting technique knowledge. Right now I'm forecasting seasonal contact patterns, so the simplest model I can understand with seasonality is a ...
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1answer
55 views

Rolling Window Forecasts in R [duplicate]

I have a question: how do I use rolling window forecasts in R: I have 2 datasets: monthly data which I downloaded from Google. monthly data I downloaded from the CBS (central bureau of statistics ...
2
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1answer
53 views

Time Series Data Mining Library?

Can anyone recommend a library for time series data mining tasks other than predictive modeling and statistical analysis? There seem to be a number for these purposes (e.g., Gretl), but nothing for ...
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59 views
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HoltWinters Vs ARIMA for high frequency time series

I am trying to forecast monthly time series with frequency/seasonal as 1008. Based on reading from RobjHyndman and CrossValidate it seems HoltWinters seasonal is ...
0
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1answer
71 views

Weighting time series coefficients using model's likelihood

I have a question regarding to time series forecasting. In particular I've been working with a Bayesian approach, but I think the question is independent from that. I have several time series which ...
3
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1answer
174 views

Determining the best correlated time series

Before asking, I read similar questions, but none of them lead to satisfying answers for my specific interest. I want to homogenize a climate time series of precipitation of the Dominican Republic ...
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18 views

Wilcoxon rank sum test for significant differences between two time points

I have data like so …(Col1:Companyname Col2:Data at timepointA; Col3:replicate Data at timepointA; Col4:Data at timepointB; Col5:replicate Data at time point B ...