A function to replace NA in the data frame based on
Jasmit Shah (10.1186/s12859-019-3250-2).
Arguments
- missdf
a data frame with missing values to be imputed containing features in columns and samples in rows.
- M
number of iterations.
Examples
data(sim_miss)
impute_bayesmetab(sim_miss)
#> X1 X2 X3 X4 X5 X6
#> 1 0.155050833 0.88115677 -0.386468709 0.1194841210 0.600405471 -1.273624037
#> 2 0.968378809 0.60748407 0.633779031 0.6181194666 0.008132938 0.752073002
#> 3 0.468263086 0.57452956 0.247608929 -0.5657341533 0.370125689 -0.004123981
#> 4 0.776819652 0.80313329 0.551339334 0.1459775318 0.724248714 0.847776059
#> 5 0.407885741 0.79911692 0.234761084 0.1897135850 0.418270750 0.708734973
#> 6 0.538797149 0.80186265 0.258614688 0.5754945197 0.238248518 -0.026157655
#> 7 0.830082966 0.75207300 0.952888095 0.0001881735 0.887881226 0.488335246
#> 8 0.187103555 0.57546133 0.856874571 0.3283282877 0.577775384 0.347228474
#> 9 0.779969688 0.94421829 -0.263212798 0.0782780354 0.739950257 0.203048012
#> 10 0.193943927 0.21898736 0.554524177 0.6041721753 0.160679622 0.739950257
#> 11 0.434231178 0.47799791 0.876943810 0.3267990556 0.529571799 0.893697520
#> 12 0.002274518 0.04466879 0.801862649 0.7904525734 0.574529562 0.574529562
#> 13 0.834692139 0.16848571 0.546737340 0.8300829662 0.960086967 0.084448704
#> 14 -0.201644334 0.36828087 0.232753204 0.8100510929 0.398616886 0.148258333
#> 15 0.956967818 0.56331137 0.602267784 0.2027530000 0.408468068 0.370281282
#> 16 0.948497073 -0.38023980 0.712539106 0.5060450307 0.613321482 0.861177622
#> 17 0.600729976 0.73432757 0.648903601 0.5206679751 0.706590850 0.836681799
#> 18 0.261807405 0.70365677 0.187562416 0.0842680801 0.799116918 0.740547051
#> 19 0.643034251 0.73682406 0.238392889 0.2687653562 0.161331222 0.985765802
#> 20 0.526233507 -0.16692996 -0.002156285 0.8147157354 0.885932416 0.032081822