lubridate (>= 1.7.4), dplyr (>= 0.8.3), ggplot2 (>= 3.2.0),
reshape, reclin, stringr, xgboost, caret, strex

Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020)
<doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.

Prioritizing Cancer Drugs for Interested Cancer
c(
person(given = "Junwei", family = "Han",email = "hanjunwei1981@163.com",role = c("ctb", "cre")),
person(given = "Jieyi", family = "Di",email = "dijy_0419@yeah.net",role = "aut"),
person(given = "Baotong", family = "Zheng",email = "btzheng1116@163.com",role = "aut"))
Prioritize candidate cancer drugs for drug repositioning based on the random walk with restart algorithm in a drug-drug functional similarity network. 1) We firstly constructed a drug-drug functional similarity network by integrating pathway activity and drug activity derived from the NCI-60 cancer cell lines. 2) Secondly, we calculated drug repurposing score according to a set of approved therapeutic drugs of interested cancer based on the random walk with restart algorithm in the drug-drug functional similarity network. 3) Finally, the permutation test was used to calculate the statistical significance level for the drug repurposing score.
Junwei Han [ctb, cre],
Jieyi Di [aut],
Baotong Zheng [aut]

Generates Prior Distributions for Proportions
Translates beliefs into prior information in the form of Beta and Gamma distributions. It can be mainly used for the generation of priors on the prevalence of disease and the sensitivity/specificity of diagnostic tests.

Differentially private regularized logistic regression

Differentially Private Regularized Logistic Regression
PrivateLR implements two differentially private algorithms for
estimating L2-regularized logistic regression coefficients. A randomized
algorithm F is epsilon-differentially private (C. Dwork, Differential
Privacy, ICALP 2006), if
|log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon
for any pair D, D' of datasets that differ in exactly one element, any
set S, and the randomness is taken over the choices F makes.