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

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73 views

How to predict a time series with seasonal pattern in R

I have data set (download from here), this data set is occupancy level in an office building within 30 days. There is a seasonal pattern daily as you may easily understand. I tried ...
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1answer
60 views

CausalImpact on single time series

Today I have tried to play a little with CausalImpact R-package https://google.github.io/CausalImpact/CausalImpact.html (Brodersen et al. 2015) to explore the impact of some decissions in a sales data ...
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24 views

Trend modelling interpretation

I have estimated the following two models: $$ Δy_t=0.015-0.410Δy_{t-1}-0.220Δy_{t-2} $$ and $$ Δy_t=0.400+0.00145t-0.150y_{t-1}-0.325Δy_{t-1}-0.220Δy_{t-2} $$ (Note that $y_t$ is the log of monthly ...
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1answer
29 views

Panel regression with only 18-24 data points (months) per category

I have data on monthly purchases of a certain type of product for different brands over the last several years. I also have estimates of consumers returning to the market to buy a new product. This ...
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20 views

Testing for structural break in the covariance

I estimated a bivariate VAR(p) model and assume that there exist two covariance regime $\Sigma_1$ for the period 1 to $T_B$ and $\Sigma_2$ for the period $T_B+1$ to $T$. I am now interest in testing ...
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16 views

What DFT of finite binary sequence means

Zero component of DFT of binary data is always real and it's physical meaning is the number of 1s in the sequence. Therefore, the ampltitude of zero harmonic is the mean of the sequence. The question ...
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1answer
49 views

Predicting water levels based on rainfall stats

I am curious if R or any other open source code can deal with forecasting changes in water elevation based on a predicted/forecasted value of rain. I have a ton of data that shows water elevations ...
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18 views

Compare distributions in time series

I have a time series (weekly sales data), on which i have made an intervention analysis (to be specific a VARIMAX). The intervention (increased opening hours) ended out being insignificant. But what i ...
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2answers
42 views

Suggested software to compute seasonal arima model

My issue is really simple: I need to compute a seasonal arima model on traffic data (5 min frequency). The data exhibits daily seasonality (288 observations). This is causing me issues in computing ...
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304 views

Time series books? [duplicate]

Can anyone recommend good books on time series analysis suitable for an intermediate level biostatistician. preferably with examples in R. Thanks in advance.
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1answer
55 views

Measure the similarty between two sequences of letters

I'm trying to measure the similarity between two time-series sequences of letters with different lengths (e.g. s1=[A;A;A;C;B], s1=[Q;A;A;A;A;A] ). The order is very important. (e.g. s3=[A;A;A;C;C;C;C] ...
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1answer
86 views

Test of significance for a nonlinear trend in time series analyses, ARIMA

I have water temperature data consisting of monthly means for 20 years. As one would expect there is a definite seasonal/cyclical pattern. I wish to model the time series data by fitting an ARIMA ...
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53 views

Attrition Forecasting

I am currently trying to develop a forecast for monthly subscriber attrition that allows me to predict for a future point in time, how many subscribers I have. I have a couple of years worth of ...
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0answers
14 views

Autocorrelation for Time-series Crossection data

I am examining whether the market reaction (Y) is influenced by a number of X's variables. My data is gathered per firm at time t. If I understood correctly, this is called Time-series Cross-section ...
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0answers
23 views

Seasonal adjustment question, why do days matter?

I have a simple ols equation where the independent variable is total production in a month. I seasonally adjust the data with an x12 and run the ols and get my estimates. The strange thing is, if I ...
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1answer
88 views

How to determine “trendiness” of a time series

I'd like to be able to compare two timeseries as to their level of "trendiness" to determine which trends better. For example, assume two stocks, Google and IBM. Would like to understand approaches to ...
2
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1answer
56 views

How “interesting” a data series is

I have a large dataset containing several objects. Each object has many attributes which is arranged in a time series. Is there a suggested method to find the top n "most interesting" attributes? The ...
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1answer
21 views

Rolling samples, choosing a number of observations

I want to estimate a forecasting equation for monthly data. I'm essentially trying to find out how to balance the stability of using a longer time series to estimate the equation versus the fact that ...
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0answers
29 views

OLS and stationarity

I am using a time series data set and my question is, if my one or two variables are stationary at level I(0) and the other variables are stationary at first difference I(1) then can I use ordinary ...
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1answer
36 views

Can I calculate 'average call duration' from 'concurrent call count' and 'started call count' per periods of time?

I got two time series with samples per period of 5 minutes: A pink: Max concurrent calls B green: Count of calls started Can I estimate the duration of the calls? ...
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2answers
60 views

Approaches to modeling data like this in R

A couple years ago I performed a linear regression on data that looked like this: ...
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0answers
39 views

regression controversies

How can I test the relationship between my independent variable (in my case Price-Earnings ratio) and dependant variable (value of market deals), if I have a wide range of values of deals (400 deals ...
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3answers
62 views

Interpreting moving average chart

Using 26 years monthly price of coconuts I plotted the 2 period, 3 period and 4 period moving average charts. Every line seems to lie overlapped. What can I infer about the trend from this chart?
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11 views

Using F-Statistic and Critical Value to infer Chi Square and P-value

I'm currently running the Granger Causality Test on MATLAB to determine whether the behavior of a set of swaps affects another set of swaps. However, my MATLAB code only appears to be producing ...
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19 views

Address the problem of heteroscedasticity

I have 15 variables. The aim is to conduct Granger's causality test. I want to see whether I should Use log for all my variables. In order to check for the occurrence of heteroscedasticity, do I ...
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16 views

Cluster of Cluster analysis across correlated longitudinal data

I am intrigued by the Cluster-of-Clusters approach (implemented via the bioconductor package ConsensusClusterPlus) and would like to apply it to my data matrix. However, I am not sure how appropriate ...
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1answer
75 views

Is this a normally distributed time series?

I have these data, representing a time series of the sales of a product: 1485, 1068, 1368, 1236, 1926, 1550, 2249, 800, 1712, 1734, 1348, 1875 The skewness of ...
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13 views

Attributing effect of independent variables on time series data

Consider a response variable, say, sales of a company. This variable is time series data (confirmed by using ACF and PACF plots). The sales depend on other variables such as price of the product, ...
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15 views

Endogeneity of RHS variable with a different order of integration than the dependent variable

I want to explain (daily) natural gas prices by a set of regressors including temperature, crude oil and coal prices in a linear regression. Regarding the latter two regressors, ADF tests suggest that ...
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24 views

How is spline computed in simple time series in AMELIA

I am trying to use Amelia to perform missing data imputation in a simple time series where time is represented as minutes and each measurement is replicated 4 times. ...
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10 views

On the correlation function of a stationary time series (spectral analysis)

I am following a proof of the following fact of which I do not understand only the last step. I will post it entirely for the sake of completeness but do not hesitate to just look at my question at ...
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0answers
32 views

What is a stationary distribution?

Today I was reading about AR(1) processes and I there was something I didn't understand: For the casual solution $X(t-1)$ and $\epsilon(t)$ are independent, and when $\epsilon(t)$-s are standard ...
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29 views

Moving averages

I have 14 yrs monthly price of coconuts of a particular market. In order to identify the trend how do I know if I have to calculate 30 day, 60 day, 90 day,. . . moving averages. What is the basis for ...
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1answer
32 views

Alternatives to a one-dimensional Poisson process [closed]

Say I have "arrival" times in what may or may not be a Poisson process. I can think of at least three ways in which it can deviate from a Poisson process: Clumping. One arrival is likely to be near ...
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39 views

Estimating probability of observing greater than X events based on a current population and historical rates

Let's say I have a population that varies from month to month, and per month, there are X number of failures. Based on historical rates, I am trying to find the probability of observing Y or greater ...
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2answers
43 views

DLM package, issues about specifying models with time-varying coefficient

I've been working on DLM package for the past few weeks. I've read the package manual and the paper written by Petris "dlm: an R package for Bayesian analysis of Dynamic Linear Models", but I am still ...
2
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1answer
42 views

How to identify relationship between response time series(Yt) & input time series(Xt) only in terms of Yt-1 & Xt?

I have a response time series(Y) & Input time series Xt & Zt. My only objective is to identify functional form Yt=f(Yt-1,Xt,Zt) where f(Yt-1,Xt,Zt) contains only lags of Yt , Xt & Zt as ...
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16 views

Dickey-Fuller Test

I am very new to R, and am really struggling to interpret the results. This is for the CHF-USD exchange rate returns for 1999-2015. What is the "cut off" % the ADF test uses, so when can i reject the ...
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1answer
41 views

Using ARMA model for future forecasting

I just started learning about times-series modeling and I'm confused by the following scenario: Let's assume we train a ARMA(p, q) model on a time-series $\{x_1, x_2, ..., x_t\}$. Later in a test ...
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16 views

What are some major theories on picking the right number for the sample window size in time series analysis?

for example the number of samples to run the moving average, or the number of samples for sequential hypothesis testing. Or if there is a control scheme going on what is the best time window for an ...
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30 views

Resources for machine learning for time-dependent data

For the past year, I have spent the majority of my free time learning a variety of ML techniques (boosting, random forests, neural nets, SVMs etc.), but I have not been able to find a lot of material ...
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26 views

Finding descriptive statistics on particular days on the time series

I got a time series of returns for the last 15 years. I would like to extract the descriptive statistics on last Thursday of every month. Suppose, if I add a filter for last Thursday of every month ...
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38 views

Empirical Prediction interval for time series forecast based on quantile regression

As Gardner notes "almost all point forecasts are wrong", so prediction intervals (PI) are necessary to quantify uncertainty and help us make informed decisions. There exists theoretical PI, and in ...
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8 views

How to determine the optimal time averaging window

I have two large time series datasets with some background noises. I would assume the two datasets are either lag correlated or lead correlated. I tried to use time averaging to smooth out the dataset ...
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0answers
13 views

How to derive the CRB for FIR blind equalization

Fast Maximum Likelihood for blind identification of multiple FIR channels presents the CRB expression on Pg 10 which is $CRB(dB) = 20 \log\left(1/|h|| \sqrt{\operatorname{tr}(\mathbf{F^{-1}}})\right)$ ...
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9 views

Statistical distances and time series of distributions clustering

I am interested in clustering $N$ time series of $T$ 'values' each. These values are distributions (which can be represented by their cumulative distribution functions (cdf), or their probability ...
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15 views

query regarding independent dummy variable in tobit regression

i have a limited dependent variable which ranges from 0 to 1 as the review of literature suggested that tobit model is to be used. But, on my limited dependent variable i want to check the impact of ...
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28 views

mean square distortion of quantization data set

I am using the matlab function lloyds to cluster a 1-dimensional timeseries. [partition,codebook,distor] = lloyds(training_set,initcodebook); and I get that the ...
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22 views

How to treat non stationary independent variables when our dependent is stationary under co-integration?

I am conducting Grangers causality test. I have 14 variables. My dependent (y) and 12 independent variables are found to be stationary at first difference. But the remaining 2 dependent variables are ...
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19 views

Multivariate time series regressions in R

I've never done time series analysis before and I was hoping to get some tips/steps on how to go about doing so. Outcome: n=39, t=60 multivariate time series of monthly sales of n goods ...