Qq normal #51
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Qq normal #51
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…ecified and modified name of post_start/end to start/end_post
previously, the QQ-normal transform was actually using a uniform random dataset to match, so it was not a normal transform, the box-muller transformation converts the uniform data to a normal distribution first.
Prevents the number of QM segments from exceeding the number of data points (in either dataset)
The QQ-normal transform will create negative values, so data with an, e.g., threshold of 0 will get lost Code not tracks any points below the specified threshold and enforces that it is below the QQ transformed data Note, it may be worth trying to do something more general for other transforms for various other thresholds
Previously the offset value of a lower quantile was not set if the slope from the previous quantile happened to be 0 This may not have had much effect because if it was not set, this value should not (or should rarely?) get accessed(?) In at least a few cases it seems to be a problem though
Previously, an updated logistic threshold (related to QQ-normal transform) was not getting passed around properly, that is fixed Also, the non-smoothed observations were not properly passed in in a few cases to calculate the logistic or residuals for time smoothed data, that is fixed.
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Merge @gutmann's qq_normal (experimental) changes into develop.