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Thread: which regression model for time series?

  1. #16
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    Re: which regression model for time series?




    Quote Originally Posted by Sylviastat View Post
    Yes.

    This is the output:

    Logistic
    Model Summary
    R R Square Adjusted R Square Std. Error of the Estimate
    .995 .990 .990 .014
    The independent variable is Year.


    ANOVA
    Sum of Squares df Mean Square F Sig.
    Regression .569 1 .569 2771.558 .000
    Residual .006 27 .000
    Total .575 28
    The independent variable is Year.

    Coefficients
    Unstandardized Coefficients Standardized Coefficients
    B Std. Error Beta t Sig.
    Year .984 .000 .370 3166.533 .000
    (Constant) 537904.449 338891.324 1.587 .124
    The dependent variable is ln(1 / SEAsia).


    Is A- contsant, B- year? where is C?........

    After further reading it seems that I will have to estimate A (upper asymptote - population ceiling), but which is B and which is C from the above output? please help.

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    Re: which regression model for time series?

    Quote Originally Posted by Sylviastat View Post
    After further reading it seems that I will have to estimate A (upper asymptote - population ceiling), but which is B and which is C from the above output? please help.
    Correct, if you want to fit the logistic function using linearization, you must estimate a independently. Honestly I don't quite understand what transformation SPSS did for you (it says the dependent variable is (1/SEAsia), which I can't quite fit in with the logistic model?).

    If you use a nonlinear procedure instead, you can fit all three parameters simultaneously.

    (The program Past does this automatically by first setting a to the max value of the data as an initial guess, then estimating b and c by linearization and regression, then optimizing all the parameters with the Levenberg method).

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    Re: which regression model for time series?


    Quote Originally Posted by ohammer View Post
    Correct, if you want to fit the logistic function using linearization, you must estimate a independently. Honestly I don't quite understand what transformation SPSS did for you (it says the dependent variable is (1/SEAsia), which I can't quite fit in with the logistic model?).

    If you use a nonlinear procedure instead, you can fit all three parameters simultaneously.

    (The program Past does this automatically by first setting a to the max value of the data as an initial guess, then estimating b and c by linearization and regression, then optimizing all the parameters with the Levenberg method).
    Thanks. I think I got it. It's the curve estimation function.

    Here is the area and the equation:

    y=1 / ( 0 + 13677.83972385804 * 0.9853271471417606**x )

    graph doesnt want to copy...

    But I think it's ok. It is South East Asia. Based on the above formula, I can announce that he population of South East Asia in 2025 will be 730,423,364

    Next ARIMA, but that will be a long process..........

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