Open jason-neal opened 7 years ago
scipy.stats.chi2(df).isf(1-probability) is used to determine the chi2 values to use.
e.g. (df, prob)
(1, 0.68 (1 sigma)) = 1
(3, 0.99 (3 sigma) = 11.30
This can produce the chi2 table.
From AVNI 1976 you go up the chi2 value from the minimum chi2 to reach the parameter values for the given confidence levels.
Take the difference Delta chi2 from minimum value
Nuno suggests making a parabola line his lithium 6 paper.
For each parameter. Pick the chi2 value that is smallest and we should get a parabola.
He also suggest adding a variable normalization that is thrown away at the minimum chi2. I could add another broadcasted parameter and multiple 1 model or obs by 0.98 and 1.02 and then reduce back to minimum chi 2 for each.