math/

bootstrap_mean.pro

top source bootstrap_mean

Math

result = bootstrap_mean(values, nboot=nboot, conflimit=conflimit, uniqlist=uniqlist)

Calculates the mean and a confidence limit on the mean based on bootstrap resampling.

Return value

Returns a 3-element vector containing the lower limit, mean, and upper limit.

Parameters

values in: A vector of values whose mean and error is to be calculated.

Keywords

nboot in: Number of bootstrap resamplings. Default: 1000.
conflimit in: Confidence limit. Default: 0.68 (equivalent to 1sigma for a normal distribution).
uniqlist in: If independent points are associated with more than one element of Values, then they should all be included or excluded together in the bootstrap resampling. In this case, set UNIQLIST to the result of running UNIQ on a list with the same length as Values containing the unique identifier associated with each. Note that for this to work, Values must be sorted in order of the identifier.

Examples

    Compares the expected error in the mean of normally-distributed values
    to the bootstrap-determined error:

    IDL> vals = RANDOMN(seed, 100)
    IDL> vals = 2.5*RANDOMN(seed, 100)
    IDL> PRINT, BOOTSTRAP_MEAN(vals)
         -0.26419502    -0.014198994      0.22447498
    IDL> PRINT, 2.5/SQRT(100)
         0.250000

Author information

History:: Written by: Jeremy Bailin 12 June 2008 Public release in JBIU

File attributes

Modification date:	Wed Apr 15 16:07:53 2009
Lines:	87

Documentation for jbiu/

Generated by IDLdoc