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

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How do I handle nonexistent or missing data?

I tried a forecasting method and want to check if my method is correct or not. My study is comparing different kinds of mutual funds. I want to use the GCC index as a benchmark for one of them but ...
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how could i handle with missing data or non existent data? [duplicate]

i tried a forecasting method and i want to check if it is correct or not and why? my study is about evaluating mutual funds for two kind of them it is a comparative study and i wan to use gcc index ...
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22 views

Regression model for predicting life expectancy

I have average life expectancy at birth data for an 8 year period and I would like to use that 8 year period to predict the trend for average life expectancy for the next 5 years. I would then like to ...
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1answer
36 views

Time series with correlated observations: How to start analysis?

We have a time series dataset: Daily arrivals of asylum seekers. Goal is to model this variable. In particular we would like to attempt Arima modeling and/or fitting a distribution. Before we get to ...
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12 views

Statistical Significance of Turnaround Time

My laboratory recently implemented MALDI-TOF MS for identification of gram negative rods in blood cultures. I collected data retrospectively from laboratory reports comparing the time from isolation ...
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13 views

What is the Fourier Transform of a brownian motion?

I looked into this article http://en.wikipedia.org/wiki/Brownian_noise and it says that: If we have a brownian motion $W(t) = \int _{0}^{t} dW(s)$, then given that the spectral density of white noise ...
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59 views

How to prove that the Fourier Transform of white noise is flat?

If we take $X_n$ a series a random vector with its components each having a probability distribution with zero mean and finite variance, and are statistically independent. How do we prove that the ...
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5 views

Method to estimate times of individual impulses from composite response

I have a detector that registers a sequence of "hits" over a period of time. Each hit produces a signal that has the approximate form ...
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1answer
14 views

Significant autocorrelation in time series decomposition random component

I'm very new to time series analysis. The data below represents about 8 years of aggregate daily visitors to some tourist attractions. I'm trying to examine the random component of some time series ...
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32 views

Detecting a trend to increase, in a time series, in real time

Probably, someone who's into technical analysis of share prices eats stuff like this for breakfast. Me, I couldn't devise a theoretically acceptable approach. I have this thing (private working set, ...
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19 views

Adding predictor variables and/ or systematic judgement to time series forecasts

I have a ways to go with my forecasting general education --- but I'm doing a seasonal time-series forecast for predicting sales order volumes. It's mostly software sales, which does have a ...
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15 views

Early stopping methods for ANN applied to series prediction

Could anyone give advice or links to advice on early stopping methods for ANN trained with back prop applied to time series prediction? I know some methods for classification tasks but don't the ...
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1answer
35 views

Peak Hours for Tweeting

I am trying to figure out the peak hours during a 24 hour period for my companies twitter account. We are trying to find the sweet spot to optimize our interactions (RT+Replies+Favorites). I have ...
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2answers
36 views

Time Series Anomaly Detection with Python

I need to implement anomaly detection on several time-series datasets. I've never done this before and was hoping for some advice. I'm very comfortable with python, so I would prefer the solution be ...
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8 views

Why does glmnet in caret give different predictions for different alphas even though lambda is zero?

In R, when using caret to train an elastic net regularization model, I find that different values of alpha give different predictions when the lambda parameter equals zero. This should not be the ...
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36 views

Test for autocorrelation

I wanted to test if there's significant autocorrelation in my data. Here's the reproducible code(R!) and the result. It looks like that dwtest and bgtest and acf are all too much different. Can ...
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23 views

Does the density of daily data impact forecast accuracy?

I know it might be trivial but does the density of daily values impact the forecast accuracy? For example, if a call center receives less than 50 calls for weekdays and less than 10 calls for weekend, ...
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25 views

mixed results for stationarity tests and structural breaks

Following situation: I want to forecast a time series of the number of trucks on the motorway in some country. Here how the regular week looks like: I have data for 4 years and divide the huge time ...
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15 views

Correlation on ordered subset

Imagine a hypothetical scenario in which a ball is thrown along a straight line. During flight, the position is continually sampled; however, at some distance, the sampling fails and only noise is ...
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1answer
32 views

Multiple regression model

I have a multiple regression equation which as four quarters (maybe called them as parameters) ...
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17 views

“Iterating”? For MA and AR processes

I am not sure what is being done here, but I keep seeing statements like Given $X_t - \phi X_{t-1} = Z_t$ $...(1)$ then $$X_t = -\phi^{-1}Z_{t+1} + \phi^{-1}X_{t+1}$$ $$ = ... $$ $$= ...
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19 views

Statistical test: Does actual time series data deviate from forecast?

I have made a prediction of future sales based on an ARIMA model. The ARIMA model is based on past data, during which there has been no marketing activity. During the period predicted by ARIMA, I will ...
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30 views

“Frequency” value for seconds/minutes intervals data in R

I'm using R(3.1.1), and ARIMA models for forecasting. I would like to know what should be the "frequency" parameter, which is assigned in the ts() function, if im ...
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10 views

Finding ACVF and two random variables

let $X_t = 0.5X_{t-1} + Z_t$ where $Z_t$ ~ $ WN(0,\sigma^2)$ I want to find the ACVF of both $X_t$ and $Z_t$, but I am a little bit confused. Say for $X_t$ $$\gamma(h) = Cov(0.5X_{t-1} + Z_t, ...
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1answer
17 views

How to construct appropriately reverting geometric AR(1) process?

Suppose I have a mean-reverting AR(1) type process, $X_{t+1} = X_t + \theta(\mu - X_t) + \epsilon_t$ where $\theta > 0 $ and $\mathrm{Var}(\epsilon_t) = \sigma^2$. This process is clearly ...
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30 views

Determine the causes of change in time with mixed models

I have a database with several continuous variables measured in two times. I searched for a change in time in my dependent variables in this way: ...
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22 views

Organizing data using time series multivariate regression?

I am trying to understand how I can organize the following data since none of what I learned in my undergrad econometrics course works. I am running out of ideas. I am trying to measure how the ...
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15 views

standardization within time series and across groups (nested data)

I read through the previous threads concerning standardization of variables, but unfortunately have not found an answer whether it is justifiable or necessary to z-standardize values across groups ...
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1answer
36 views

Stochastic Volatility Model

In Kim et al. (1998) stochastic volatility model is specified as: $y_t=\beta\exp({\frac{h_t}{2}})\varepsilon_t,\quad t\geqslant1$ $h_{t+1}=\mu+\phi(h_t-\mu)+\sigma_\eta\eta_t$ $h_1\sim ...
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46 views

How to implement a simple Bayesian Network for Time Series Data?

I'm a computer science grad student, with not much knowledge in Bayesian statistics, so I'm seeking for guidance for the simplest start. I have 10 variables, like demand, price etc. and I want to ...
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28 views

What is the source of nonstationarity in this VAR model?

I am trying to forecast a VAR model, which consists out of 5 variables with a monthly frequency. The problem is that the VAR model produces an unstable forecast and I am not sure what the source of ...
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1answer
20 views

Calculation of Higher-Order Cross-moments

How can I calculate standardized central cross-moments for 2 time-series? The 4th-order standardized central moment, kurtosis, is; ...
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33 views

Reverse engineer a predictive model from a time series graph

I have found some real estate plots in a scientific article. These graphs mainly describe, the believes of the author of the development of the real estate market in the future for certain countries. ...
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1answer
49 views

Outlier Detection in Time-Series: How to reduce false positives?

I'm trying to automate outlier detection in time-series and I used a modification of the solution proposed by Rob Hyndman here. Say, I measure daily visits to a website from various countries. For ...
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16 views

How to merge overlapping discontinued data time series?

I have two datasets consisting of the US Federal debt held by Federal banks with a timespan covering the period 1953Q1 to 1988Q4 and 1970Q1 to 2014Q2. (series FDHBFRB and FDHBFRBN from the FRED ...
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32 views

STL-decomposition of a time series with deterministic trend and seasonality

what is the relationship between STL-decomposition and deterministic components of time series like trend or seasonality? I have a time series with deterministic trend and deterministic seasonality, ...
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19 views

Unit root in shares

Suppose that dependent variable is a share of sth (for example it is a % of positive answers to the same question in each period of time t). If data shows the unit ...
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3answers
115 views

How do I detrend time series?

How do I detrend time series? Is it ok to just take first difference and run a Dickey Fuller test, and if it is stationary we are good? I also found online that I can detrend the time series by ...
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1answer
21 views

Matching two power signals for similarity

Below are the images of two signals that i plotted. Both the signals are from fridge belonging to different houses. Visually looking at the plot i can tell that these plots belong to fridge as they ...
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23 views

Longitudinal data: baseline effect versus random intercept 2

My question follows this post: Longitudinal data: baseline effect versus random intercept The topic is very interesting and I have two further questions, one very practical and another about ...
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21 views

Cross correlation of two power signals

I have two devices and their power usage data. I am trying to see how co related these two devices are. i.e If i use device 1 then how often i am using device 2. It will be helpful if anyone can ...
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31 views

PCA on spatial precipitation data time series

I have precipitation time series data stored in a 3D matrix called 'pre' (dim1/2=position (index), dim3=time). I want to do a principal component analysis in order to detect the main variance and thus ...
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9 views

Extract ocasional peak and recent trend from noisy time series with threshold driven sampling of an impulse signal

I have event sampled time data for several measurements for a large number of units. The data is recorded only when the measurement is above a threshold. The measurement amplitude increases, and then ...
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1answer
68 views

ARIMAX with a specified nonlinear model using the arima function in R

I am interested in fitting an ARIMAX model using R. As known, ARIMAX can be understood as a composition of ARIMA models and regression models with exogenous (independent) variables. I have a time ...
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21 views

How to improve linear model generalization when autocorrelation is present?

I have features $X_t$ and response $Y_t$ (all continuous variables) and my objective is to find the best estimate of $f(X_t)=Y_t$ where $f$ is linear, and 'best' is defined as lowest generalisation ...
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61 views

What's the minimum sample size required to do a time series analysis?

I'd like to know the minimum number of monthly data points required to do time series analysis with the seasonality effect in forecasting. I read some articles & they were saying that 50 or 60 ...
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+50

Predicting Y from a regression model for dY

I have some time series data where I'm modelling temperature as a function of various predictors. On physical grounds, I can expect that $$\frac{dT}{dt} \propto T_a - T$$ where $T_a$ is the ambient ...
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48 views

Time series with autoregressive error

How can I in R fit a time series, $x_t$, with external regressors, $v_t$, and an autoregressive error? This time series model is given as follows, $x_t = \beta v_t + \epsilon_t$ where $\epsilon_t = ...
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1answer
32 views

Multivariate Time Series Forecasting in R - data in 10 minute intervals

I have data where an observation was made in 10 minute intervals for 8 weeks. I have around 170 variables that were measured every 10 minutes. I am trying to use multivariate time series analysis to ...
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What does a linear/geometric probability in time series mean?

In some discrete time series I analyzed I'd like to interpret whether there is a meaning to the observed probability model. The data is some discrete time series with a population of objects which at ...