Files in kkdey/classtpx
MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

#.gitignore#

.Rbuildignore

.gitignore

DESCRIPTION

NAMESPACE

R/.DS_Store

R/class_count.R R/class_topics.R R/class_topics_2.R R/class_tpx.R R/class_varselect.R R/count.R R/fash.R R/tpx.R README.md

classtpx.Rproj

inst/CITATION

man/counts.Rd man/predict.topics.Rd man/rdir.Rd man/topicVar.Rd man/topics.Rd

src/.DS_Store

src/Makevars

src/latools.c

src/latools.h

src/rhelp.c

src/rhelp.h

src/topics.c

test/deepnet.R test/limsolve_ex.R test/test1.R test/test_classtpx.R

vignettes/classtpx-vignette.Rnw

vignettes/classtpx-vignette.log

vignettes/classtpx-vignette.pdf

vignettes/classtpx-vignette.tex

vignettes/classtpx-vignette.toc

vignettes/figure/structure_leng-1.png

vignettes/figure/structure_leng_1-1.png

vignettes/figure/structure_leng_2-1.png

vignettes/figure/structure_leng_3-1.png

vignettes/figure/structure_ortholog_classtpx_omega_fix_3-1.png

vignettes/figure/structure_ortholog_classtpx_theta_fix_3-1.png

vignettes/figure/structure_ortholog_maptpx-1.png

vignettes/figure/structure_scialdone_classtpx_omega_fix_3-1.png

vignettes/figure/structure_scialdone_classtpx_theta_fix_3-1.png

vignettes/figure/structure_treutlin_classtpx_omega_fix-1.png

vignettes/figure/structure_treutlin_classtpx_theta_fix-1.png

vignettes/figure/structure_treutlin_classtpx_theta_fix_2-1.png

vignettes/figure/structure_treutlin_classtpx_theta_fix_3-1.png

vignettes/figure/structure_treutlin_maptpx-1.png

vignettes/utilities/ensembl_classtpx_ex.Rmd

kkdey/classtpx documentation built on May 20, 2019, 10:34 a.m.

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kkdey/classtpx
MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

Files in kkdey/classtpx
MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

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kkdey/classtpx MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

Files in kkdey/classtpx MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

R Package Documentation

Browse R Packages

We want your feedback!

kkdey/classtpx
MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.

Files in kkdey/classtpx
MAP Estimation using topic models in a semi-supervised set up where there are few samples with known topic proportions or known to belong to some cluster exclusively and there are samples for which no such information are available.