autocorrelation

  1. M

    Two ways to include temporal autocorrelation

    Hi, assume that we have time series with autocorrelated values described by the regression model Y_i ~ X_i. As far as I understand, in AR-regression models, this correlation is considered by assuming that residuals are autocorrelated. Instead, I could introduce additional predictors...
  2. helgasaraswati

    Autocorrelation With Breusch Godfrey Serial Correlation LM Test R Commander

    This Is One Method For Detecting Classic Assumption of Autocorrelation Using Breusch Godfrey Serial Correlation LM Test. It's Using Software R Commander. This is the Autocorrelation Tutorial With Breusch Godfrey Serial Correlation LM Test R Commander.
  3. B

    Non linear mixed effects model and autocorrelation

    Hello everyone ! I am working on a non-linear statistical mixed effects model using package nlme in the R software.. The response variable is a cumulative flux of carbon dioxide, representing soil carbon mineralisation, during soils incubation at controlled temperature and humidity. The...
  4. S

    Forecasting with autocorrelation present

    Hello, if one is to compare different lag orders for forecasting (and minimize RMSFE, root mean squared forecast error) for lets say autoregressive models and the datagenerating process is an AR(4) model. Thereby using an AR(3) model to forecast one should expect worse RMSFE values than an AR(4)...
  5. M

    Dealing with temporal autocorrelation

    Hi, assume we have a measured value for each year from 1990-210, and we want to estimate a linear trend. Now there is a problem of autocorrelation, i.e., the measured values do not scatter randomly around the fittet line but rather resemble a "smooth function" wriggeling around the linear fit...
  6. K

    Sample size estimation for multinomial autocorrelated data

    I'm trying to work out the minimum sample size needed to accurately characterise land cover data. The idea is to set out the a number of quadrats across the study site and identify what land cover type occurs in each. I have an idea as to how many categories there should be. So this is a...
  7. L

    Partial Autocorrelation Function

    Hello everyone, I am preparing for a test and I have came across a question I am having problems with: Calculate partial autocorrelation of first and second order in the fillowing model: y[t]=-0.7*y[t-1]+e[t]+e[t-1] any solution or hints on that?
  8. K

    How to correct for autocorrelation in Excel

    I do not understand how to correct for autocorrelation. One website easily describes how to do it in excel however I could not find any sources to verify this: https://analysights.wordpress.com/tag/data-analysis-using-microsoft-excel/ This is the site that explains how to correct, however...
  9. F

    Violating Linear Regression assumptions

    I have a dataset in which I am performing linear regression with multiple covariates. The goal of the analysis is to identify important covariates (categorical and continuous) which have an important effect on the response. This is a natural resource dataset so it is not as clean cut as other...
  10. consuli

    3 Lines Matlab Code to R Code (Generating autocorrelated random values)

    Hello, I have found the following Matlab Code for generating autocorrelated random values, with a defined autocorrelation on lag 1. Source: http://www.mathworks.com/matlabcentral/newsreader/view_thread/102939 a1=0.5; A=[1,-a1]; # A=[1,-a1] <=> A= c(1, -a1) x=filter(A,1,randn(1000,1)); #...
  11. consuli

    How to generate an autocorrelated random variable?

    Hi, I know I can generate two correlated random variables x1 an x2 using x1= z1 x2= c* z1 + sqrt(1- c^2)* z2 Where z1: standardnormal random variable z2: standardnormal random variable c= Correlation(x1, x2) But how can I generate an autocorrelated variable x, autocorrelated on x(t-1) ?
  12. noetsi

    cox regression

    This is interested in surival time to an event and deals with time series data inherently, including the use of lagging indicators in some cases. Many of the independent variables can change with time. Discussions I have seen do not address concerns with autocorrelated data or bias tied to...
  13. M

    Regression with cointegrated time series data

    Hello, I am studying a predator-prey relationships using field data collected biannually over 5 years. For example, here is some abundance data: pred,prey 23.0,0.1 31.5,0.7 18.0,1.4 26.0,2.6 25.5,3.3 36.7,5.0 52.3,20.9 38.7,11.1 47.0,13.9 43.3,13.7 I wish to estimate the numerical response...
  14. D

    Urgent Help needed regarding r1 Autocorrelation

    I'm searching from past 2 hours on the internet and I'm unable to find a solved example of calculating r1 first coefficient of correlation from the successive observations on timeline. Sixteen successive observations on a stationary time series are as follows: 1.6, 0.8, 1.2, 0.5, 0.9, 1.1, 1.1...
  15. M

    Controlling for autocorrelation in a regression

    Hi all I have a panel data; I ran the Hausman test and it showed a significant p-value, thus I conduct my regression by using 'xtreg' command + fixed effects, vce (robust). As I understand 'robust' option is for heteroscedasticity. I checked my variables for multicollinearity and did not find...
  16. K

    Autocorrelation of discrete time series

    I am currently planning on calculating the autocorrelation for various lags given a time series. However, my elements of the time series are "discrete" and abstract classes; i.e., no integers. For example, my series could look like: class A, class B, class A, class A ... Of course I...
  17. G

    Johansen Test For Cointegration‏

    Hi, I am a student from Belgium and I am making a thesis about the relationship between credit aggregates and property prices. I examine the Granger-Causality between the two variables and I also do some conintegration tests. I have a question about the latter. What are the conditions for...
  18. B

    Interpreation of flat correlogram - ARMA model

    I have been asked to build an ARMA model for some oil WTI spot prices. I have manipulate the data to make it stationary (taking log-returns), and stationarity has been confirmed by the Augmented Dickey Fuller test and all the other stationarity tests available in EViews. However, when I...
  19. S

    Understanding expectation operator notation

    Hi, I am trying to understand how to interpret a problem that uses the expectation operator. Please see the attached pdf for more information. Could someone explain in words how to read the definition of Yk that uses the summation operator? Why would the mean of Y equal 0? I think I am...
  20. P

    No collinearity between dependent and exogenous variables - Implicatrions

    I'm trying to test for autocorrelation in the residuals of an AR(p) model. The stata output is: "the exogenous variables may not be collinear with the dependent variables, or their lags" and no results. Can I conclude from this that the residuals are not autocorrelated? Thank for answering...