Comments (1)
FBartos
commented on June 26, 2024
Hi,
The first error message indicates that you have too few z-scores in the range from 1.96 to 6. The estimation algorithm uses only statistically significant z-scores to estimate the mixture model (z-scores larger than 6 are treated separately and combined with the remaining data later). You can check that with sum(df$z_score > 1.96 & df$z_score < 6) or visually check with a histogram.
The sample data bug looks like nothing I encountered so far. I just tested and I could run the examples with the newest version of the package and Rcpp. Could you please attach the printed output of utils::sessionInfo() ?
Cheers,
Frantisek
from zcurve.
Related Issues (13)
- Won't run even on the example dataset HOT 1
- Not explicitly labelling p-values as an argument HOT 2
- add observed discovery rate to output HOT 4
- A bit unsure how to begin HOT 4
- Option to change the default CI HOT 4
- List of Articles - script? HOT 1
- fit z-curve (mixture model) with all z-values rather than only statsitically significant ones HOT 4
- plot zcurve object using ggplot(2) HOT 2
- relationship between z value and replication rate HOT 4
- How does z-curve deal with censored p-values? HOT 1
- False discovery rate HOT 1
- Misleading error message when empty vector is passed HOT 4
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from zcurve.