Preconditioned Conjugate Gradient Algorithm for solving Ax=b
The package solves linear system of equations Ax=b by using Preconditioned Conjugate Gradient Algorithm where A is real symmetric positive definite matrix. A suitable preconditioner matrix may be provided by user. This can also be used to minimize quadratic function (x'Ax)/2-bx for unknown x.

Reconstruction of Causal Networks for Data with Random Genetic
Effects
Willem Kruijer, Pariya Behrouzi, Maria Xose Rodriguez-Alvarez
pcalg, graph, Matrix, stats, MASS, utils, Hmisc, methods,
lme4, sommer, ggm
Implements the pcgen algorithm, which is a modified version of the standard pc-algorithm,
with specific conditional independence tests and modified orientation rules.

Implements the pcgen algorithm, which is a modified version of the standard pc-algorithm,
with specific conditional independence tests and modified orientation rules. pcgen extends
the approach of Valente et al. (2010) <doi:10.1534/genetics.109.112979> with reconstruction of
direct genetic effects.

Piecewise Constant Hazards Models for Censored and Truncated
Data
Using piecewise constant hazards models is a very flexible approach
for the analysis of survival data. The time line is divided into sub-intervals;
for each interval, a different hazard is estimated using Poisson regression.

Piecewise Constant Hazard Models for Censored and Truncated Data
Piecewise constant hazard models for survival data.
The package allows for right-censored, left-truncated, and interval-censored data.

Bayesian Network Learning with the PCHC Algorithm
c(person("Michail", "Tsagris", role = c("aut", "cre"), email = "mtsagris@uoc.gr"))
Bayesian network learning using the PCHC algorithm. PCHC stands for PC Hill-Climbing. It is a new hybrid algorithm that used PC to construct the skeleton of the BN and then utilizes the Hill-Climbing greedy search. The relevant paper has been submitted and is currently in revision.

Bayesian Network Learning with the PCHC and Related Algorithms
bigmemory, bigstatsr, bnlearn, Rfast, Rfast2, robustbase,
stats
Bayesian network learning using the PCHC algorithm. PCHC stands for PC Hill-Climbing. It is a new hybrid algorithm that used PC to construct the skeleton of the BN and then utilizes the Hill-Climbing greedy search. The relevant paper is: Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics (Accepted for publication). <doi:10.1007/s10614-020-10065-7>.