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

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Statistical test for comparing the power spectrum of two signals

Question: What statistical test can i use to compare the power spectrum of two signals? I have two signals whose time-series representation and power spectrums (also in log scale) are shown below: ...
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10 views

the decision of being White noise on e-view

And for example, let's take SMA(2) model in this table does there exist white noise ? Which value I observe to decide the existance of white noise? Please explain it. Thank you
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23 views

White noise ACF - PACF

I found PACF and ACF like the following table . But, how can I decide whether there exists white noise? And what is white noise? If there is no white noise, can I say being stationary?
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1answer
7 views

Extract ETS method used for automatic forecasts of hierarchical time series with hts package

I'm trying to extract the ETS method that is automatically chosen when we apply the forecast function to an hierarchical time series using the hts R package. When I look in the structure of the ...
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0answers
9 views

Identities in a VAR model

I am working on a VAR model where one of the equations is an identity. For example: $$ \begin{cases} A_t = \alpha_{11} + \alpha_{12} A_{t-1} + \alpha_{13} B_{t-1} + \alpha_{14} C_t + ...
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9 views

r package for non-decimated /stationary wavelet [on hold]

Which r package is should be used for forecasting and plotting stationary wavelet transformation?
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9 views

calculating stationary wavelet by pyramid algorithm [on hold]

would someone explain how to calculate Stationary wavelet by pyramid algorithm?
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2answers
41 views

Autocorrelation and Partial Correlation plots in ARMA models

Consider the following input and its Autocorrelation and Partial Autocorrelation plots (source). What are the shaded blue areas in these plots? I often see them when studying ARMA models. What do ...
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0answers
5 views

Help in state and parameter estimation when a time series model excited by pseudo binary input

An IIR system is excited by a pseudorandom binary signal $z_n$. The output of the system is corrupted by zero mean additive white Gaussian noise and this is observed, i.e., $y_n = \mathbf{h^Ty_{n-1}} ...
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11 views

Time series analysis for discontinous years

i have a data of measured values of pH in river water for two years 2004 and 2009 for each month. I want to see seasonal trend ie: are there similarity in summer , winter and monsoon for both year. ...
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26 views

Incorporating intraday data into end-of-day forecast

my target variable is observable intraday but I am interested only in EOD forecasts. I will denote the variable $\ y_{D,24}$ as the reading of interest for day D is ...
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0answers
4 views

Interpretation of Lo.Mac M1 and M2 test statistics

I used R to get the Lo.Mac test result for a return series. I am not sure how to interpret the M1 and M2 test statistics of Lo.Mac variance ratio test. What are the critical values to reject or accept ...
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4answers
80 views

Detecting changes in time series (R example)

I would like to detect changes in time series data, which usually has the same shape. So far I've worked with the changepoint package for R and the ...
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0answers
4 views

How to find anti-correlated subsequences in correlated time series?

Say I have two time series $X_t$ and $Y_t$ (with $ 1 \leq t \leq N$), which have a high positive Pearson correlation. Say I also have reason to believe there are subsequences $X_{tj}, Y_{tj}$ (where, ...
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2answers
30 views

Let's talk sales forecasts - integrating a time series model with subjective “predictions/ leads” from sales team

I've learned a lot about time series forecasting this previous year, but one thing that's still a bit lacking in terms of a formal system is integrating a future sales projection into an existing time ...
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0answers
22 views

Which program for PVAR? [on hold]

I have been looking at some studies that use panel vector autoregression models. The problem is, I can't find which statistical package the authors use. I would like to estimate impulse responses in ...
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0answers
13 views

Technical Indicators reference [migrated]

I have been looking for a good reference where I can find how technical indicators of stock market analysis are calculated. I have a dataset (time series) which I want to extract these indicators to ...
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2answers
40 views

Detect periodic events within data

I have a collection of card transactions, each with a date, amount, card identifier and merchant. I want to determine if a card is making periodic payments to a given merchant. The issue is that the ...
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0answers
18 views

Multivariate stochastic time series forecasting in R

Hi I have a multivariate time series like this ...
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0answers
12 views

Slope versus Slope Change [on hold]

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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1answer
46 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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0answers
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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0answers
5 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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0answers
31 views

Matlab: Problem in implementaion using toolbox while learning Kalman FIlter

I have AR(1) model with data samples $N=500$ that is driven by a random input sequence $x$. THe observation $y$ is corrupted with measurement noise $v$ of zero mean. The model is $y(t) = ay(t-1) + ...
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1answer
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
32 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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0answers
32 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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13 views

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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18 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 ...
2
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0answers
10 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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0answers
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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1answer
25 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
28 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
33 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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65 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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24 views

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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1answer
152 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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27 views

how to predict the time when event occurs

I have time series data. The data looks like the following: ...
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0answers
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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1answer
27 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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7 views

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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1answer
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 ...
2
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1answer
53 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 ...
3
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3answers
171 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 ...
3
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2answers
40 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 ...
3
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1answer
95 views
+50

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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18 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) + ...