Thread: which regression model for time series?

1. Re: which regression model for time series?

Originally Posted by Sylviastat
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.

2. Re: which regression model for time series?

Originally Posted by Sylviastat
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).

3. Re: which regression model for time series?

Originally Posted by ohammer
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..........