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

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Slope versus Slope Change [closed]

Is there a difference in the definition of Slope versus Slope Change? I am doing slope and level change calculations for my dissertation. I can't seem to find the answer if there is a difference.
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50 views

Detecting anomalies in a time series where new data points will be continuously added

I have a time series data and I will be adding more data points in a consistent manner. I want to figure out whether the new data point added is an outlier, in regards to the previously observed data ...
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20 views

Decomposing a known time series into a linear combination of known timeseries.

I'm have a time series that is dependent on a large number of other timeseries, but these dependent timeseries don't add up to the main one, as I don't have the full population of these dependent ...
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7 views

What Model to Use, are my assumptions correct? Psuedo Time series

I have quite a few questions and would like some help/advice or a general pointing i the correct direction. I have a dataset that has every home sold over the last 3 years and it's sale price, along ...
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99 views
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Beginner level: Help in learning Kalman Smoother (Part 1)

Parameter estimation of Linear Dynamical system is a tutorial which explains Kalman Filter, Smoothing, and Expectation Maximization. I have followed the derivation for Kalman Filter. But cannot ...
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30 views

Regressing a discrete variable

I have a discrete dependent variable (say, number of units bought) and want to run a linear regression with in-store promotion, seasonality, trend etc. as predictor variables. I'm not sure if it is ...
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1answer
38 views

Normalize time series with different lengths with linear interpolation in R

I have a large set of time series (100k, each 3 observations), their lengths varies about 10% on average. Each of them cover the time interval of the same lengths but varies due to rate of sampling, ...
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35 views

AIC versus cross validation in time series

I am interested in model selection in a time series setting. For concreteness, suppose I want to select an ARMA model from a pool of ARMA models with different lag orders. The ultimate intent is ...
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Prediction intervals for mixture models for time series forecasting - is it really an average of the prediction intervals of the averaged models?

I'm trying to find out how to do forecasting with a mixture model (averaging the forecasts of an ets, an arima and an ...
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21 views

how i can model VAR-GARCH

i really need your help how i can run the ling and McAleer(2003) model (VAR-GARCH) and McAleer (2009) model(VAR-AGARCH) with spillover response? and can you help me how i can run DCC-EGARCH with ...
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11 views

time series with error bounds at lower level than “series”

I have what I think is a very basic question but I am greatly struggling with knowing what model to use and where to start, and all help would be appreciated. Basically I have a dataset that is a ...
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11 views

What interpolation methods to use for irregularly sampled time series?

I have two AR(1) time series with a pre-defined cross correlation from which I sample using a Gamma distribution to obtain irregular time series. What interpolation methods can I use to obtain a ...
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29 views

Unit Root testing and stationarity of a time series

I'm trying to understand: how is check for stationarity(or lack thereoff) linked to unit root testing. More so the logic of it. i understand the null hypothesis used in adf or kpss but I need the ...
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1answer
32 views

Where do you find info about which predictive distribution an algorithm uses for forecasting?

I am trying to fit a mixture model to a time series in order to make forecasts. I'm told that this is quite straightforward as long as the predictive distributions used by the component algorithms ...
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20 views

Level of a time series and adding daily dates to plot

just wondering if you can help me with explaining this plot Just wondering what does level tell me? is it the trend of the data with seasonality taken out, which is the slope right? Can't seem to ...
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1answer
34 views

Regression with different frequency

I am trying to run a simple regression but my Y variables is observed on a monthly frequency and x variables are observed on an annual frequency. I will really appreciate some guidance on a suitable ...
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1answer
16 views

What statistic to use to measure effectiveness of treatment on fluctuating process

I have a process $R$ that normally does something like a random walk between 0 and 1. I have a set of treatments. I believe that some of the treatments will bias the process $R$ in such a way that, ...
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66 views

ARMA model in R

I am a bit confused using the arma() function in R regarding interpretation. So what exactly is the equation of a for example AR(1,0,2) given the output AR1, MA1, ...
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13 views

Help forming a VAR model

Can anyone help me for a very basic VAR model for regressing Inflation (CPI first difference) on energy prices and money supply. any suggestions be appreciated.
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How to use lagged dependent variables (panel data) in practice?

Working with a panel data set with a daily time series structure I was told to include a lagged dependent variable. The dependent variable is daily electricity consumption of a medium size sample ...
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157 views

Interpretation of (scale of) AIC, AICc and BIC when comparing different models

I'm trying to fit a model to a time series, but I am pretty confused as to which is the best. I'm looking at an arima model, and ets model and an stlf model, which each performed best within their ...
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28 views

how to predict the time when event occurs

I have time series data. The data looks like the following: ...
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18 views

Passing different forecasting method to hierarchical time series forecast in R? [migrated]

I have a hierarchical time series, the bottom level series of which all exhibit intermittent demand. It seems advantageous to use Hyndman's HTS package for optimal combination within the hierarchy. It ...
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29 views

Stationarity of AR(1) process whose autoregressive parameter could change over time

Imagine an AR(1) has an autoregressive parameter which could change in time. $y_t-\mu=\phi_t (y_{t-1}-\mu)+\varepsilon_t\,$, where $\phi_t$ is not always constant but still lies inside the usual ...
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How to add NA's to the data not available for some dates? [migrated]

I have a data for short term electricity load forecasting. I have to clean the data, adding NA's in the data for dates( and blocks) with no data. For example: 1st case: with some dates missing: ...
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27 views

Seasonal Indexes adding to zero

In the textbook Forecasting: principles and practice by Hyndman and Athana­sopou­los, in the Classical Decomposition (Sec 6.3), in step 3 of the additive decomposition algorithm, the authors state ...
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55 views

ARIMA Specification from Correlogram

How should I determine the data generating process from the correlogram below? This is non-seasonally adjusted monthly data that has been 1st differenced. I am trying to conduct univariate time ...
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3answers
173 views

How can you tell if a yearly increase in population is statistically significant?

I have daily data for two years consisting of "number of sightings" each day. Is there a way for me to test whether the data for year 2 is "significantly" higher than the first year? I know the ...
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2answers
41 views

Symmetry in moving average smoothing in “Forecasting: principles and practice”

In the textbook Forecasting: principles and practice by Hyndman and Athana­sopou­los, in the moving average smoothing section (Sec 6.2), the authors speak of even order moving average smoothing not ...
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138 views

Measuring length of intervention effect

I ran a study in which participants were randomized to either a control or an intervention, with outcomes in the form of time-to-event data. While overall time-to-event is shorter in the intervention ...
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19 views

Autoregressive Model

I am currently attempting to build a regression model explaining Current Inflation as measure by monthly CPI. I am considering the following model; CPI = B0 + B1(LAG_CPI) + B2(Lag_Oil_Price) + ...
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16 views

Vector Autoregression, how to interpret Impulse Response Function (IRF)

I have an IRF that shows the GDP shock to GDP. Let's say I have a 5-year forecast of GDP. If there is an immediate 1% decrease in GDP today, can I adjust the original 5-year forecast by using the ...
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51 views

Interpretation of the autocorrelation plot

This plot indicates the autocorrelation for a monthly time series of household gas consumption. This plot clearly shows a seasonality, I was wondering if the repetitive positive and negative ...
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43 views

Issues in auto.arima algorithm when using external regressors and outlier correction

auto.arima is an automatic arima modeling function in forecast package in R that uses information criterion(example: AIC/BIC) to ...
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tbats{forecast} in R gives strange predictions for some folds in cross validation

My daily data shows weekly and yearly seasonality, so I decide to try the tbats function. When I first fit the model with all the data, it worked fine. However ...
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1answer
18 views

Choosing the right model for prediction

Given a set of temperatures of different cities for a month, which prediction model should I use for a two day look ahead prediction? Regression models or Time series?
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226 views

A 'Pure' Time Series Model

Can anyone explain to me what is meant by a 'pure' time series model? I believe it might have something to do with the exclusion of external factors but I'm really not too sure. For example, the ...
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35 views

Analyzing Independently Pooled Cross Sectional data (TIme series)

I am new with time-series data analysis. It seems that there is some confusion in terminology (Panel, and time-series cross-sectional). But my question is general in nature. How do I analyze a ...
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Time series causation and probability

I have a series for an individual that looks like this: There are observations of the individual at random times. At each time they may experience an event and the outcome fo that event is binary ...
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1answer
19 views

Using regression tree on time series data

I have been looking around for resources on applying a regression tree in an attempt to understanding how various spend variables impact a companies revenue overtime. Is this type of analysis ...
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1answer
36 views

Forecasting daily demand for next year

I have two years daily demand data, corresponding to which I have to forecast the daily demand for next year. I am new to time series, and used Arima model for this purpose. But it predicts only about ...
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44 views

Estimate the unique permutation of a vector that fits a desired spectral density

Lets say I have a vector of 10,000 random data that follow a predefined distribution. Is it possible to find the unique permutation of this vector (without modifying its values) that matches as ...
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1answer
38 views

Are linear processes stationary?

I am reading Soren Johansen's book on cointegration and I'm wonder about the following definition: Definition 3.1. A linear process is defined by $Y_t=\sum_{i=0}^\infty C_i\epsilon_{t-i}$, $t=0, ...
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1answer
28 views

Time Series Unobserved Components Model

I have real price data for 55 years and want to study its trends. for this i am trying to estimate the Unobserved Components (UC) Model. Which software will be better eviews or stata? Also what are ...
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Seasonal Kendall test and the Mann-Kendall test

I am trying to detect trends using non-parametric methods but I'm a little confused as to when you should apply the Seasonal Kendall test. Don't get me wrong I know you apply it when you have ...
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37 views

Statistical comparison between two curves

I have two time course experiments of the same study, and I want to determine if the time course curve is statistically significant or not. Let's say I treated a group of people with drug A, measure ...
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2answers
100 views

Unable to get suitable forecast for ARIMA model in R due to outliers— attached code for easy replication

Using the attached data that has been recently updated I am not able to obtain a statistically significant forecast. The data is extremely seasonal. The data is stored here for easy replication: ...
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2 views

Using R Time Series to show plot value/volume pairs over time [migrated]

Is it possible to use R's timeseries functions to plot clusters of value/volume pairs for a year? Example, I have a data frame with over 500k observations across 21 variables. Three of those ...
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24 views

How to incorporate exchange rates in a multi-country econometric model?

I have for 12 countries variables related to the trade of one specific commodity (production, consumption, import, export, trade costs, and international prices). The data range is 2000-2013 with a ...