time series

  1. L

    Time series question

    Hi, If I have a time series that has a normal distribution of error from the mean is there a technique that lets me forecast the next period based a stronger weighting for recent months. I suppose I can work it up but wondered if anything exists. Thanks in advance.
  2. A

    Arma model fitting

    Below is my data. Only lag 2 is significant in both pacf and acf plot.EACF says it is ARMA(0,2) and I think it can be. However,if it is, aren't there supposed to be tailing off in PACF and significant both 1 and 2 lag. I put some plots and model fitting result below. I am waiting for your...
  3. R

    Problem of maximum likelihood estimation of time series

    Hi everyone, I have a problem of how to calculate the MLE for a given time series data set. I have read the book Statistical Method for Forecasting, there are some example of building AR model but it simply stated that the MLE are the multiple of two quantities. I have no idea on how these...
  4. C

    Estimate the coefficients of an equation system - can I use OLS?

    Hi! I have not worked so much with this type of regressions and have tried to find the answer in my econometric books and on internet, but have unfortunately not had any luck. I appreciate all help I can get with this! Im using time series data to measure the rate of return of the inputs...
  5. C

    Time series - Selecting limited time period to regress

    Hi, I have a time series with monthly data from 1871 till 2014 which I can run regressions on. However I would like to run several regression on limited periods from the data, for example 1930-1980 and 1980-2010. How do I tell stata to only run the regression on this limited period...
  6. E

    Regression Analysis with Time Series Data

    Hey guys, I have some monthly time series data and I'm trying to perform regression analysis on it. I'm just wondering, if I have a few insignificant months does it make sense to remove their parameters from the model? It marginally increases my adjusted R-squared, but I'm just wondering if...
  7. D

    What test to determine if 5 years of population data has a trend?

    Hello. I have population data for 5 years for several species of birds and I would like to know whether the populations are growing, staying stable, or decreasing. I am using R. So far, what I have been doing is creating a linear model of the count data (or log of the count data) by year...
  8. F

    Augmented Dickey Fuller Test

    How do you test for non-stationarity using an augmented Dickey Fuller test with no time trend and a lag of 2 or more in STATA? I need simple regression commands (i.e. "gen...", "reg...", etc..). I am a beginner with STATA. Thanks!
  9. N

    Correlation to determine the best reference series for homogenization

    Before asking this, I read similar questions, but none of them lead to satisfying answer for my specific interest. I want to homogenize a 64 years (1940-2003) climate time series of precipitation of Dominican Republic. For that, it is really important to select a reference series among a group...
  10. A

    Exercise in Stationarity

    Hello everyone, I am Alexandra I am completely new to the forum and have no IDEA about statistics. My boyfriend is at his final semester of his BSc in Economics and he is such an idiot he wants to quit. Why? Because he can't pass one course of statistics called "time series analysis and...
  11. C

    Stationarity vs. iid

    Hi all, I came across a statement about iid and stationarity which says that it is unrealistic to assume stock returns to be i.i.d but rather strict stationary. Can someone explain to me what the difference is? Strict stationary means that the returns at time t, t+1, ..., t+n are equally...
  12. P

    First PCA component versus mean

    Hello, I have a question regarding PCA. I have 10 time series (highly correlated in low frequencies) and run standard PCA. I am curious about the reasons why the first principal component has almost 100% correlation with mean of these 10 series. Can anyone explain it to me please? Thank you!
  13. T

    correlating two time series (no homework!)

    Hi everybody. I have a question and although I've spend really a lot of time searching, alas, I haven't found an answer. I want to argue there's a correlation between two time series (variables x and y for 1960-2010). I've seen charts and they do seem to develop similarly. But I was asking...
  14. S

    Time Series Forecast

    I have a time series data of hourly consumption of electricity for 720 data points and I want to make a forecast for 25 time points after the 720th time point. I am using the software R for this purpose. First I have decompose the series into three parts: (i) Trend (by method of Moving...
  15. W

    Time Series and Rolling Regression Using Stata

    Hi, I tried to run rolling regression on some inflation rates data and plot the coefficient values with Stata 10 but couldn't get the results I want. Below are some selected Stata codes [not the full set] I used: //my data are yearly inflation rates [variable "inflat"], and the duration is...
  16. S

    [Time series models] covariance in MA(1) process

    Hello, the following question is about a stationary MA(1) process (Moving Average of Order 1) - see attached image. Epsilon represents white noise, i.i.d. E(epsilon) = 0. Can someone please help me understand the last part of the bottom equation? I do understand the term inside the...
  17. M

    Tim series Analysis in EViews

    Hello Everyone,I have a question which may be very simple .For Example I have estimated ARIMA(1,1,4) from a data having sample 1961-1999.To produce forecast I re-estimate sample from 1961-1995 and then its easy to produce forecast on eviews.I want to confirm forecast produced by EViews manually...
  18. X

    sparse time forecast

    Hello to All I have a dataset pertaining to 1980 and 2000. Because I have actual value in 1980 (CR80) and 2000(CR00); I want to make a model that is a forecast for the data point in 2000 using the value in 1980. I want to use covariates from 1980 to predict how good the forecast is. What...
  19. T

    Distributed lag modells (for Marketing Mix Modelling)

    Hi there, I am actually trying to build a marketing mix modell for a retail company with R. I have a dataset from 2009 to 2013 and per calender week the following information: - sales volume - average temperature - GRP TV - GRP Radio - GRP Out of Home - Volume leaflets - GRP online...
  20. L

    VAR model for multivariate time series

    so using a model var with the package 'vars' for R, in this way: model_var <- VAR(my_data, lag.max=10) roots(model_var) pred <- predict(model_var, n.ahead=15) if my_data is stationary there are no problems. But, if my_data is not stationary, I differencing all the time series in...