comparing two bootstrap distributions

wolfzinke_at_gmx.net
Date: 02/02/05

  • Next message: Martin: "Re: 3D Surface plot in R" 
    Date: 2 Feb 2005 03:28:10 -0800

    I need some advice in a procedure, where I am not sure it is valid the
    way I am using it.

    I want to compare the parameter of curves (gaussian) fitted to two data
    sets.
    Both data sets consists of 8 mesured values, where I have got 20 data
    points. Original I did the fitting using weighted least squares to the
    mean values for each of the eight values.
    To get confidence intervals I used a bootstrap procedure. 100 times I
    took a new sample for each value (sampling with replacement)and fitted
    the curve to the mean values for the new samples. For each fit I
    determined the fitting parameter (amplitude, sigma, center, offset),
    thus I ended up with 100 values for the parameter for each of my data
    sets, which allows me to determine the median value of each parameter
    and its confidence intervals.
    Now I want to test each paramter, whether they are significant
    diffferent from each other. The obvious method would be to use a
    Wilcoxon sign rank test, where I compare the 100 values from each
    parameter. Is this a valid method or do I need somehow to consider the
    fact, that the distributions, I want to compare, are a result from a
    bootstrapping procedure?

    I hope someone is able to give me some advice or maybe references for
    further information.

    Thank you for the support.

  • Next message: Martin: "Re: 3D Surface plot in R"

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