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

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What if the trend is changed?

I want to forecast tourist arrivals using time series analysis. I expected to use monthly data from 2000-2013. But due to the civil war, the trend was changed after 2008 as in the following plot. ...
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16 views

NARX model to predict future values

I have this problem , where I have to predict a value of a indicator which depends on 270 other predictor variables. I read the time series modelling and prediction on MATLAB , which took the example ...
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26 views

My transfer function has non-stationary inputs, but a stationary output. Should I difference both the inputs and outputs during structure estimation?

I have a system of two inputs and one output that I'd like to model using the following Box-Jenkins transfer function ("dynamic regression") structure: $$y_t=\frac ...
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2answers
71 views

How to check if a series has been seasonally adjusted correctly?

I am a bit puzzled here and would like to understand how to check if a time series has been seasonally adjusted correctly using X-13 Arima. After seasonally adjusting time series using X13-ARIMA ...
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24 views

Very different Neural Network test errors for same architecture

So I'm doing a time series prediction, and assessing the capability of the ANN to predict that time series. I am using Matlab's neural network toolbox functions, and the training parameters are the ...
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70 views

are qqplots appropriate for time series?

I've seen that qqplots are a very useful tool to check model assumptions. In particular to analyze the residuals. However, it seems that is based on data ordering and therefore assumes a atationary ...
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11 views

How to compare the volatility of quarterly p&l of two firms in the same sector?

I want to compare the volatility of the historical quarterly profit and loss (p&l) data of two or more firms operating in the same sector and determine whether the volatility of p&l of these ...
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32 views

Is it reasonable to use a combination of two forecasting models for a dataset?

I used tbats to fit a model for a 3 years of historic data and the values work fine but as I did not include holidays, holiday predictions are really off. I used arima with regressor (holidays at ...
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56 views

Bartlett's Sphericity Test for PCA Failure

I am using XLStat for a PCA of time-series water chemistry data. I have 23 analytes and 29 samples. I am using a correlation matrix for PCA as I find it more interpretable in the context of ...
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42 views

Find the median individual with observations on multiple variables over time

I have a question regarding the use of median. We collected data concerning disease development on hosts. We gathered the evolution of three variables over time on individuals. Their characteristics: ...
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94 views

Obtaining the SarimaX equation from the arima coefficients

I have a SarimaX model with three regressor variables: ...
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18 views

Synchronize time series by date and time in R

e.g. i have two time series that describe how much money in specific currency i spent at specific date: ...
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50 views

Time series - plotting continuous and categorical variable

I have one dependent continuous variable and an independent categorical variable. Each one minute window on a time series is marked with one category, for example 10:00 - 4, 10:01 - 1, 10:02 - 5, ...
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18 views

multidimensional time series nonlinear parameter estimation

I am trying to fit time series data for performing parameter estimation of a nonlinear multidimensional dynamical model (grey-box). At the moment I'm successfully using MATLAB's ...
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22 views

What type of model should I use? (Time series, univariate, dependent variable is a count)

I have a univariate model in which I am looking to predict the number of articles per week in a newspaper about a protest (count data) by how many arrests of protesters occurred per week. I have 148 ...
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1answer
49 views

How can one say if a model is poor based on RMSE value

I have a general question about the value of using RMSE to see if a forecasting model is poor. I used the forecast package in R to find forecasting models for ...
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8 views

Use cases for P-Kernel for SVMs

I've been reading the book by Cristianini on Kernels (2004) where generative kernels (like p-kernel and fisher-kernel, not to be confused with polynomial kernel!) are described. I am interested in ...
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31 views

What statistical analyses should one perform on ensemble forecasts (given a measurement)?

I have an ensemble of time-series predicting a scalar variable. Additionally, I have a measurement time series of this scalar variable. Which statistical analyses could and/or should I perform to ...
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130 views

How to characterize abrupt change?

This question may be too basic. For a temporal trend of a data, I would like to find out the point where "abrupt" change happens. For example, in the first figure shown below, I would like to find out ...
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247 views

How to find the functional form of pdf from time series using Kernel density estimate

I will appreciate help in determining the functional form of the probability density function (pdf) for the following case. I have read about Kernel Density Estimate for the case when we don't have ...
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26 views

prediction for data including weekly and annually seasonality and dummy variables for holidays

I have a three years of daily data for number of orders a trucking company receives everyday. Number of orders are high during weekdays and they have a huge decrease for weekend. I used msts to ...
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43 views

prediction using historic data with unusual annual trends

I have 4 years of daily data. there is a decreasing trend for the data for the first 3 years but the trend increase for the 4th year. I wanted to find a fitted model using the first 3 years and then ...
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2answers
262 views

Wrong predictions for weekend, but good predictions for weekdays

I have a set of 3 years of daily data. I saw weekly and annual seasonality in the data so I used msts time series and tbats ...
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37 views

predicting time series with support vector machine using R

I am planning to do time series prediction using support vector Machine. I could not find any materials about time series application of support vector machines using R or Mat-lab. Similar question ...
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77 views

Time series forecasting accuracy measures: MAPE and MASE

We come to this toy example showing MAPE and MASE are not consistent when measuring forecasting accuracy. Data consist of 100 white noise and 100 $AR(1)$ time series with length $N=500$, mean $\mu=1$ ...
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17 views

Normalized RMSE

I have several time-series in a VAR(1) and, due to some of them haven't the same unit of measure, I'd like to estimate the RMSE in percentage. I know that it could be done in several ways (see below) ...
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72 views

Stock closing price forecasting using ARIMA model in R

I have downloaded the daily stock Adjusted Close price of one stock from sep 2011 to till date. As per my study plan, I have plotted some basic plots to understand the daily stock Adjusted closing ...
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31 views

Standard model for time series with (possibly multiple) seasonal component

Suppose you have a "new" way to formalize a seasonal component and you want to see if your method is worth to be published. My idea is to take a "standard" model for time series with seasonal ...
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84 views

Does Stationarity for Time Series extend to Independent Variables?

There have been many questions about the importance of stationarity and also its means of calculation here on CV, but one question that I have not seen an answer to is whether or not stationarity (in ...
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28 views

Data with weekly and annually seasonality but the first day in time series is not the begining of a week

I know it might look naive but I have a very basic question. I have a three years of historic data which has weekly and annual seasonality. January first as my first data is on Wednesday so my time ...
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8 views

regression test or two bloc PLS model to prove a gene expression matrix relationship

I have two gene expression matrices, matrix A coming from a set of two hypothetically different cells while matrix B is coming (for certain) from only one of them. The structure of a gene expression ...
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41 views

Detecting a step change in time ordered data

Suppose I have data which looks like this: ...
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46 views

Problem in ARIMA Model in R

I am running ARIMA model in R and I used auto.arima(X) function to decide appropriate model.After using this function I found that the order of my model is ARIMA(2,1,0). The problem is I run the same ...
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53 views

Difference between the forecast and simulate functions in the {forecast} package in R

I have been using the forecast package in R to make forecasts based on an ARIMA model and have noticed a difference in the output of the forecast and simulate functions when calculating confidence ...
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1answer
46 views

No fitted ARIMA model

I wanted to fit an ARIMA model to a daily database for three years but auto.arima couldn't find a model and showed the following error: ...
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Design study choice for multivariate time series data

I am involved in a research project in which we have data about students and their learning activities. We have two courses C1 and C2 and in each course students communicated using some of the three ...
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68 views

Validate a Markov Chain with few states (model switching)

Suppose I have a five state Markov chain. The states are observable (in fact I defined them, they are outcomes of an classification algorithm). So I have a long time series, see the first picture. ...
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23 views

Metrics to compare time series results with no defined truth standard

I have several (~10) models which all predict time series results for a specific problem (hourly heat loss from a building over a year). I do not have any measured data or truth standard results to ...
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1answer
116 views

Forecasting a seasonal time series in R

Forecasting airline passengers seasonal time series using auto arima Hi, I am trying to model some airline data in an attempt to provide an accurate monthly forecast for June-December this year using ...
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17 views

what is the best prediction interval for a forecasting model with daily and annually seasonalitis?

If we have a data set which has daily and annually seasonality, is it reasonable to use the forecasting model for one year ahead? I mean, I want to have a 48 hours forecast for a logistic provider ...
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34 views

Creating auto arima for two following time series with two different non linear slopes

I'm trying to model (and predict) the following time series, which consist of two periods (enrollment period and non enrollment) as the following: I believe that this model should consist of two ...
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15 views

model specification for SARIMA order (2,1,2)x(0,1,1) period 12 [duplicate]

Good morning scholars. Please am fitting a Seasonal Arima model of this form: (2,1,2)x(0,1,1) period 12 but I don't know how will look like. Can anybody help me wit the model specification? Thanks.
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42 views

Fitting ARIMAX with lagged X variable (Matlab)

This question is divided into two parts. I currently have a Y vector with 364 data points (Y) and an exogenous variable (X) with 364 data point. X is a good predictor for Y that I want to pair up ...
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24 views

What does a fitted value mean in dshw forecasting package?

I have a double seasonal data. I wrote the following code to find the best fit model and find fitted values: orders <- read.csv("DataForR.csv", header = TRUE), NumOrders <- orders$Orders, ...
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32 views

Quantity like correlation

I want to calculate this sort of quantity, $f()$, for my data. $x$ and $y$ are time series. $f$ behaves like a pseudo-correlation, but is different in the sense that even if the values jump up and ...
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1answer
49 views

Transforming a time series with a negative number

I have been given data to forecast however it has a negative figure within the data which then, when doing a log transformation to make the series stationary, the ARIMA script i have written won't ...
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1answer
51 views

Regressing a differenced variable on a lagged variable. How can I fix the error in R?

I have a time series (std) of 324 observations with no missing values, starting from January 1987 and ending in December 2013. I want to regress via OLS the one in the question. In R, the code: ...
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35 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
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25 views

Initiator follower analysis with time series data sets

I am a newbie to this forum. I searched different white papers and codes on google but couldn't find a solution, that's when I registered on this forum.. Please share in case you guys have a idea as ...
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Python module request: Spectral density estimation for multivariate time series

I have worked with scipy.signal.welch and spectrum.pptm to calculate power spectral density with Welch and Multitaper methods. However as far as I can see these functions are meant for one dimensional ...