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stephenslab / ebnm

R package to fit Empirical Bayes Normal Means model.
https://stephenslab.github.io/ebnm/
12 stars 9 forks source link

add point_exponential, npmle, mode estimation for point_laplace #31

Closed willwerscheid closed 3 years ago

codecov-io commented 3 years ago

Codecov Report

Merging #31 (a6f2f4f) into master (9e6e2bb) will decrease coverage by 0.14%. The diff coverage is 93.54%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master      #31      +/-   ##
==========================================
- Coverage   91.24%   91.10%   -0.15%     
==========================================
  Files          20       14       -6     
  Lines         948     1360     +412     
==========================================
+ Hits          865     1239     +374     
- Misses         83      121      +38
Impacted Files Coverage Δ
R/loglik_point_laplace.R 77.77% <75.00%> (-6.84%) :arrow_down:
R/workhorse_normal_mix.R 88.88% <75.00%> (-0.23%) :arrow_down:
R/point_exponential.R 88.94% <88.94%> (ø)
R/point_normal.R 91.66% <91.66%> (ø)
R/point_laplace.R 92.76% <92.76%> (ø)
R/ebnm.R 93.71% <97.89%> (+1.20%) :arrow_up:
R/workhorse_parametric.R 99.33% <99.33%> (ø)
R/ebnm_fns.R 100.00% <100.00%> (ø)
R/npmle.R 100.00% <100.00%> (ø)
R/opt_control_defaults.R 100.00% <100.00%> (ø)
... and 12 more

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