Compressive Sampling: Sparse signal recovery utilities
Provides miminization routines and related utilities for
compressive sampling. l-1, l-2 and TV (1-D) minimization, DFT
basis matrix, sparse signal generator and examples.

Provides miminization routines and related utilities for
compressive sampling. l-1, l-2 and TV (1-D) minimization, DFT
basis matrix, sparse signal generator, mutual cumulative
coherence and examples.

Compressive Sampling: Sparse Signal Recovery Utilities
c(
person("Mehmet", "Suzen",
email = "mehmet.suzen@physics.org", role = c("aut", "cre")))
Utilities for sparse signal recovery suitable for compressed sensing. L1, L2 and TV penalties, DFT basis matrix, simple sparse signal generator, mutual cumulative coherence between two matrices and examples, Lp complex norm, scaling back regression coefficients.

person("Nan", "Zhang", email = "awekevin@onethird-lab.com", role  = c("aut", "cre"))
Since December 2019, Wuhan City, Hubei Province has continued to carry out surveillance of influenza and related diseases, and found multiple cases of viral pneumonia, all of which were diagnosed with viral pneumonia / pulmonary infection. On January 12, 2020, the World Health Organization officially named the new coronavirus causing the pneumonia epidemic in Wuhan as "2019 New Coronavirus (2019-nCoV)". The current epidemic situation is very serious, here we developed an R package for 2019-nCoV analysis(Real-time monitoring and Visualization) by querying real-time statistics of 2019-nCoV virus cases from <https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5&callback=1580373566110> and performing follow-up analysis.

R2 Measure of Explained Variation under the Additive Hazards
Model
R^2 measure of explained variation under the semiparametric additive hazards model is estimated. The measure can be used as a measure of predictive capability and therefore it can be adopted in model selection process. Rava, D. and Xu, R. (2020) <arXiv:2003.09460>.
ahaz, pracma, zoo, caTools, survival, Rdpack (>= 0.7)