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

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How can I model a binary outcomes in time series using logistic regression?

My data has a binary outcome (attack or not attack), day (20 day in repeated measured design) and some covariates (nestling’s movement). The objectives of my experiment are testing the effect of time ...
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21 views

VaR with ARMA and GARCH in R

I have a time series of 1255 daily observations (01/01/2008 to 31/12/2012) of a stock log returns, I would like to compute the 1 day ahead VaR for the every single day (meaning for every Day I want ...
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16 views

Joint distribution R [migrated]

I have a list of 10 stocks, with each having a time series of log returns (AIG, JPM,...). I have calculated the log returns for each of the stocks as follows: ...
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22 views

Find distribution of Bus arrival time

I am currently working on a problem in my research which can be modeled into the following question: Let's say I have a rich dataset with values for the variable $A$ which is equal to ...
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5 views

how to implement link anomaly method for discovering emerging topics [on hold]

We are trying to do a project to discover emerging topics in social network via link anomaly method. But we are not knowing how to implement this.
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2answers
140 views

Do you see trends in my residual plots?

Do you see trends in my residual plots? These residuals plot show the standardized residuals against fitted values, origin period, calendar period, and development period. The patterns in any ...
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1answer
41 views

Residual based bootstrap autoregressive series in MATLAB

I have defined the model as follows. Let $$y_1 = 0$$ and $$ y_i = \alpha + \beta y_{i-1} + \epsilon_i $$ for $i_2\ldots i_T$, where $\alpha$ and $\beta$ are the estimated coefficients and ...
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4 views

simulating AR(1) process for N variables in MATLAB [migrated]

I am quite new in programming, can somebody tell whether the following approach is correct in matlab? clc; clear; N = 15; T = 221; alpha = randn(N,1); % normally distributed intercept as ...
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1answer
31 views

Help understanding how the cointegration equation for VECM models are derived

I am learning about Vector Error Correction Models from Sean Becketti's "Introduction to Time Series using Stata". While I know how to run the Stata commands to estimate the VECM, I have no idea why ...
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25 views

Using seasonality in a model

Suppose you are modeling sales of a prepackaged good and suppose there are seasonal periods in the time series. Also suppose that the brand of the prepackaged good you are modeling comprises the ...
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35 views

Prediction based on multiple time series - Python

I have 3 predictors and 1 variable that represents ground truth. They all are linked time series. My purpose is with the 3 predictors to try to forecast the ground truth data. For example : ...
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26 views

How to compare and cluster sets of daily time series?

I have multiple dataframes each representing traffic speed for each day of the year (366 dataframes for 366 days of the year). The raws of the dataframe are timestamp from 00:00 to 23:55 at 5 minute ...
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107 views

Analyse ACF and PACF plots

I want to see if I am on the right track analysing my ACF and PACF plots: Background: (Reff: Philip Hans Franses, 1998) As both ACF and PACF show significant values, I assume that an ARMA-model ...
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1answer
40 views

Bootstrapping at group level (time series data)

I have time series of continuous measurements of two different variables $x(t)$ and $y(t)$ measured at times $t_i$. I measured those variables for different subjects (with different characteristics) ...
5
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2answers
66 views

What's the model representation for the first difference of a local level model?

This is my first exercise for space state models and I've a few questions I'd need to resolve before I actually start doing the exercise. Unfortunately, I'm self teaching (I have no professor to ask) ...
2
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0answers
17 views

How to evaluate a Bayesian forecast?

Suppose that I have a predictive posterior, which is an attempt to predict some one-step ahead forecasted value $\hat{y}_{T+1}$. How do I assess if my posterior has done a good job or not? If we had ...
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26 views

How to handle autocorrelated residuals (and independent variables) in multiple regression? [on hold]

I am trying to carry out multiple regression for an air pollutant (dependent variable), and weather parameters- wind direction, wind strength, rain, air temperature, relative humidity (independent ...
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18 views

Comparison of Non-Stationary Time Series Trends

I am trying to compare two readings of the same occurrences from two different sources, forming two time series. I would like to assign a metric to their similarity/dissimilarity, but the method I am ...
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22 views

Suitable model for predicting mean output over time

I have 3 years of yearly historic data on the results of a harvest (of truffles) from multiple different areas involving multiple individuals harvesting in each area. The dataset contains: name of ...
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1answer
52 views

Is it possible to simplify linear regression if one of the variables does not have errors and is equispaced?

Specifically, I have a time series with fixed $\Delta t$ of the following form: $x_0, x_1, x_2, ... x_n$ and $t_0, t_1, t_2, ... t_n$ where $t_{i+1}-t_i =\Delta t $. I'm interested in the improved ...
3
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30 views

Maximum value of d in ARIMA model

I am trying to model a data series using ARIMA model. The series seems non stationary because the acf decays very gradually.Even after differencing two times, the values of p and q are coming as high ...
2
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23 views

Regressing nonstationary on stationary variable

I am trying to empirically estimate the coefficient for the Okun's law as a relationship between output growth and unemployment. I am using the simple gap version, where I regress real output growth ...
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25 views

Get groups in time series with categorical data in R for use in gts

I have sales data organised in a table with 6 columns (4 for the location and type data, and 2 for the dates and the quantity sold), and 24 rows for each category representing the sales over 24 months ...
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79 views

AR(q) model with F-test

I am wondering that if we have an AR($q$) model for time series: $$X_i=\beta_1X_{i-1}+..+\beta_{p}X_{i-p} + \beta_{p+1} X_{i-p-1} +...+\beta_{q} X_{i-q}+\epsilon_i,\epsilon_i \;\text{iid}\; ...
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KFAS example won't run [migrated]

I tried to get the example on page 13 of the KFAS manual to run but no luck. Anyone have any ideas? ...
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1answer
57 views

Statistically Approximating Clicks From Limited Data

Assume a business started in January 2014. I have the following daily data (from June 2014 to December 2014): 1. Number of people who joined the website; 2. Number of people who left the website; ...
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1answer
24 views

How to remove level shifts and pulses from time series?

I am interested in describing seasonal patterns in several time series and then seeing if they are related. My approach is to fit regression models with an indicator variable for each season which ...
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14 views

MANOVA on autocorrelated variables

I am trying to find out if signals 1 and 2, can explain signals 3 to 10. All signals are continuous and time-varying and are rather strongly autocorrelated. Signals 3 to 10 (my dependent variables) ...
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1answer
35 views

Using monthly product usage data to predict customer churn

I've been reading tons of papers detailing methods on predicting customer attrition, but none of them have mentioned using product usage data over time. We keep detailed logs of how many times User A ...
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1answer
39 views

What is the auto-covarriance of a stationary AR1 process?

Say a stationary AR(1) process is given by: $$ X_t = c + \phi X_{t-1} + \epsilon_t $$ where $ \epsilon_t $ is a white noise process with zero mean and constant variance $ \sigma^2 $. Wikipedia ...
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1answer
65 views

Finding occurrences of specific patterns in time series

I have to locate occurrences of Cyllinder, Bell and Funnel patterns in univariate time series $X$ of gamma-ray sensoring. This is a specific case of the general CBF synthetic problem found in a few ...
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12 views

Generating randomized time series from discontinues historical data

I have some historical data from microbiological sampling, which are not collected continuously. For example historical data are in 2008/01/12, 2008/03/25, 2008/5/30, 2009/07/05, 2009/07/29.For ...
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81 views

Testing if frequency of event occurrences over week days is uniform

I’m trying to figure out if there’s a calculation that can be done to show you have enough data to draw conclusions on trends within the data set. I have made an observation on a class of equipment ...
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63 views

How to take advantage of multiples series with the same behaviour for forecasting?

I'm quite new to statistics and forecasting, and I have to build a model to forecast monthly sales of different related products in a bunch of cities. Seasonal ARIMA seams to be a good model for ...
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15 views

How is GARCH's p estimated in software?

From what I know, the GARCH(p,q) model is estimated via MLE and through an iterative process. Let's say if i wanted to recreate a GARCH(1,1) parameter estimation with excel solver (through maximizing ...
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27 views

what is a stationary process?

I just started learning time series and this notation confuses me. For a ARMA process, phi(B)X=theta(B)Z according to some notes I found online, the criteria for the process to be causal is where ...
5
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2answers
118 views

How to use Pearson correlation correctly with time series

I have 2 time-series (both smooth) that I would like to cross-correlate to see how correlated they are. I intend to use the Pearson correlation coefficient. Is this appropriate? My second question ...
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0answers
27 views

How can I predict based on several time series of many different projects?

I want to predict the time that a client takes to pay for a service that has already been received. We are talking about a construction company, so the payments are always overdue since the company ...
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1answer
45 views

Comparing Time Series Forecast Models

I'm to write a short report on Time Series forecast comparison. I'm a beginner in the field. I want to investigate how one chooses which model is better than the other based on the forecast results. ...
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9 views

Bisecting K-mediods [duplicate]

Is there an algorithm like Bisecting K-mediods and what would its advantages/weaknesses be? It seems to me that it could be used well in combination of Dynamic Time Warping for clustering time ...
2
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1answer
92 views

Why is the arima function giving odd answers

I have a problem in interpreting what the arima function in R is doing. I have the following code: ...
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1answer
57 views

modelling time as continuous vs. discrete

I am writing an analysis plan for data that is collected on approximately 30 people at approximately 5 unevenly spaced time points. I am planning to analyze the data via a repeated measures mixed ...
2
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1answer
62 views

Time-series regression

Suppose that a typical firm determines its level of stocks $H_t$, in accordance with the following rule: $H_t - H_{t-1} = \lambda (H^*_t - H_{t-1}) + \epsilon _t$ where $\epsilon _t$ is a serially ...
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1answer
15 views

Continuous predictor of a significant difference on another scale at T1 and T2

I was wondering if anybody could point me in the right direction for a statistical test. I’m looking whether a continous variable (e.g. a personality variable) predicts a significant difference ...
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1answer
36 views

Predicting university course marks using historic data of class mean and student's own marks

I would like to predict my course marks for this year based on the data for class mean and my own marks for the past years. What would be a good starting point for a model for such kind of data? ...
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1answer
91 views

ARIMA equation interpretation

I'm trying to replicate ARIMA (1,0,1)(1,0,1) equation in excel as a formula but I am not able to understand the interpretation of white noise residual e(t) or u(t).If could help me understand the ...
2
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34 views

Visually representing confidence and standard deviation in a time series

We've been tasked with presenting a time-series graph showing 2 series of estimations each with a standard deviation and confidence. There are only 4-5 points in each series and both occur over the ...
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13 views

Change in distribution of a portfolio of customers

I'm looking for some high-level thoughts on understanding a change in distribution for a portfolio of customers. I have a file with information on a bunch of customers. These customers are purchasing ...
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1answer
26 views

Smoothing intraday data when only looking at a certain time range

I have an intraday price series (5 minute) over several months. I want to smooth the data using an ema but also i am only interested in analysing the series between certain time periods eg between 8am ...
4
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1answer
82 views

Why is the Confidence Interval Changing for this Time-Series

I have some R code (which I did not write) and which performs some state space analysis on some time-series. The data itself is shown as dots (scatter plot) and the Kalman filtered and smoothed state ...