This is a package for symmetric discrete triangular
distributions

Tristan Senga Kiess\'{e}, Francial G. Libengu\'e, Silvio S.
Zocchi, C\'{e}lestin C. Kokonendji
This is a package for general discrete triangular
distributions which is an extension of the symmetric discrete
triangular distributions

Chad Hammerquist [aut, cre],
Scentsy Inc [cph]
Use alternating least squares to estimate a Temporally Regularized Matrix Factorization (Yu, Hsiang-Fu, Nikhil Rao, and Inderjit S. Dhillon, 2015) <arXiv:1509.08333v3>
(possibly) in the presence of missing values.

Functions to estimate temporally regularized matrix factorization (TRMF) for forecasting and imputing values in short but high-dimensional time series. Uses regularized alternating least squares to compute the factorization, allows for several types of constraints on matrix factors and can handle weighted data.

Functions to estimate temporally regularized matrix factorizations (TRMF) for forecasting and imputing values in short but high-dimensional time series. Uses regularized alternating least squares to compute the factorization, allows for several types of constraints on matrix factors and natively handles weighted and missing data.

Jingyi Jessica Li <jli@stat.ucla.edu>, Wei Li <liw@ucla.edu>
AnnotationDbi, openxlsx, GO.db, gtools, RColorBrewer, gplots
A new bioinformatic tool for comparing transcriptomes of two biological samples from the same or different species. The mapping is conducted based on the overlap of the associated genes of different samples.

Jingyi Jessica Li <jli@stat.ucla.edu>, Wei Vivian Li <liw@ucla.edu>
AnnotationDbi, openxlsx, GO.db, gtools, RColorBrewer, gplots,
topGO
A new bioinformatic tool for comparing transcriptomes of two biological samples from the same or different species. The mapping is conducted based on the overlap of the associated genes of different samples. More examples and detailed explanations are available in the vignette.

A new bioinformatic tool for comparing transcriptomes of two biological samples from the same or different species. The mapping is conducted based on the overlap of the associated genes of different samples. More examples and detailed explanations are available in the vignette. For detailed description of the method, please refer to Li, Wei Vivian, Yiling Chen, and Jingyi Jessica Li. "TROM: A testing-based method for finding transcriptomic similarity of biological samples." Statistics in biosciences 9.1 (2017): 105-136 <doi:10.1007/s12561-016-9163-y>.