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...probability with se.fit=T argument in predict(), so would it make sense to get standard error for posterior probability from lda() and how? Another question about standard error estimate from glm(): is it ok to calculate 95% CI for the predicted probability using the standard error based on normal apprximation, i.e. predicted_probability +/- 1.96 * standard_error? Thanks John [[alternative HTML version deleted]]

Hi, I have a data-matrix: > CB                    Zeit                Low 2   2011-05-02 08:05:05 7596.0 3   2011-05-02 08:10:06 7593.5 4   2011-05-02 08:15:11 7594.5 5   2011-05-02 08:20:15 7597.5 6   2011-05-02 08:25:18 7595.0 7   2011-05-02 08:30:20 7593.5 8   2011-05-02 08:35:21 7593.0 9   2011-05-02 08:40:21 7593.0 10  2011-05-02 08:45:25 7599.0 11  2011-05-02 08:50:34 7596.0 12