time series

  1. M

    When to use Augmented Dickey Fuller test vs Dickey Fuller Test - Time series

    Checking a variable for I(1) process, when should i use a ADF vs DF test?
  2. A

    Time series

    I have a poverty dataset and I wish to forecast the poverty percentage of a place in the future. I only have 2 years = 2006 and 2012 data. Is time series possible? Is there a statistical way that I could include more data points in between?
  3. S

    Graphics of Time Series (tsset command isn't working due to repeated time values)

    Hey everyone, I have a question regarding the creation of graphics for time series. I have two rows with one being the study subject ( ‘1’ denoting singles and ‘2’ denoting married couples). Additionally I have a row called ‘year’ ranging from 2002 to 2012 with repeated values obviously...
  4. D

    Time series forecast. Probability of forecasted value exceeding a threshold value?

    OK. Let's say that I have several years of monthly sales data. How would I go about finding the probability that monthly sales, three months in the future, will exceed a threshold value? Is this something that's commonly done? I spent some time searching on the internet for this, but haven't...
  5. M

    ARCH-process with exponencial variance function

    I need some help for a proof regarding Engles ARCH-paper from 1982. For an ARCH-process with a variance function h_t = exp(a_0 + a_1 y_{t-1}^2) he states, that the data generatet from this model has infinite variance (or goes to infinity) whenever a_1 is not zero. I need to explain why...
  6. B

    Stationarity of time series and VAR model

    Hello, I have two variables, one is stationary I(0) and one is non-stationary I(1). Is it possible to make VAR model for these two variables if the non-stationary variable will be differenced to obtain stationary process I(0)? Thank you for any responses.
  7. Y

    how to fit the auto arima model

    hi guys, Im new to R and I got a problem unsolved for several days: I got a dataset which covers three years by week and I ran an auto arima on the train data set which is 80% of the original data set. Then I got the following result: ARIMA(1,0,0)(0,1,0)[53] with drift Im wondering how...
  8. M

    predicting a rv based on past time series results

    Hi all, I have 3 previous years data (ie 3 time series) going from 05/05 may 05 - august 25 , the curve for the current year has data plotted from may 05 to may 26th (plotted every Thursday) so how would I use the previous data to predict the curve into the future? Time Series does not...
  9. F

    Policy chance analysis - time series count data

    Hi, I need some help to determine my approach. For a school project I would like to examine the effect of a policy change in the Danish registration law for certain cars, happening in june 2007. I have a dataset with the number of registrations pr. month from jan-97 to dec-15. If I put...
  10. L

    Time series in small data with R

    Hi there I have this data year number of surgeries 2000 570 2005 1340 2006 4730 2007 5359 2009 6060 2010 6340 2014 ???? 2015 ???? I want predict number of surgeries in 2014 and 2015. I want use neural network, SVM and all methods for...
  11. rogojel

    Physical interpretation of an AR(n) series

    Hi, I am learning TS analysis but my angle is probably diffent from the usual. Being in six sigma I need to reduce the variability of a process that I can prove is basically AR(3) which with 3 runs on the average per day means one day's runs influence the next day in the mathematical model...
  12. W

    Inter-subject agreement re timings of (unequal number of) events

    Hi everyone, I am trying to figure out what would be the best statistic to use to quantify the amount of agreement that exists between subjects who were asked to press a button whenever they felt a certain emotion while listening to a short (2min) piece of music. Plotted as time series, the...
  13. W

    Time Series - Difference over time

    Hello, I'm new in the time series, so I need some help. I have a short time series (5 quarters), with the proportion of a parameter (public transport-user people). I know there are some effects of TS (trend, seasonal, cyclic and random). I would like to testing the (significant) difference...
  14. rogojel

    Interpretation of an AR model

    hi, looking at process times of a rather complex machine I found that an AR(2) model describes it quite well. Does it make sense to interpret this as an indication that the machine has a "memory" of about 2 runs ? E.g. insufficient cleaning between runs? thanks a lot!
  15. S

    What method for this problem? [Correlation / Correspondence]

    Hi, I have a data set like the following with some categorical/nominal values (like Gender and Age Group) and a ratio scaled value (DropOut, which is the week after registration in which a person dropped out of a program [so it's never zero or less, and it's not the calender week]): I want...
  16. A

    Is AR(1)-ARCH(1) covariance stationary?

    I'm becoming confused by this. Say I have the following model: I know that an AR(1) is covariance stationary if |\phi|<1. I also know that an ARCH(1) is covariance stationary if \alpha_0, \alpha_1>0 and \alpha_1<1 . If those conditions hold does that imply that an AR(1)-ARCH(1) is...
  17. T

    Multiple measurement time series

    Hi dear helper, I have a collection of monitoring data which I want to analyze as to significant differences over time. I have monitored 2 groups of people over 16 months as to how often they feed their livestock per day. Both groups are of different size and each individual has a different...
  18. A

    Covariance of Time Series

    Could someone explain if this is the right way to do it? Thank you! https://goo.gl/photos/ykmodDUj7RVKcS4W9
  19. M

    Autoregresive (AR) models and stationarity - Contradiction?

    Hello, I have a problem regarding the general understanding of autoregressive (AR) models (and related models, such as MA and AR(I)MA models) which are used to analyze time series. An important assumption in these models is that we have stationarity, which implies that the mean and the...
  20. K

    time series with bivariate data?

    I have a datetime (yearly) variable which indicates when/if a subject registered, a count of the 400,000 subjects who registered at each facility and those subjects identified as being asked a particular question upon registration, a dichotomous yes/no. The requester asked that their time to...