Description: Easy-to-use functions to explore Oracle databases and import data
into R. User interface for the ROracle package.

Title: Orca: Counting graphlet orbits in sparse graphs
Description: Implements orbit counting using a fast combinatorial approach

Title: Computation of Graphlet Orbit Counts in Sparse Graphs
Authors@R: c(person("Tomaz", "Hocevar", role = "aut"),
Description: Implements orbit counting using a fast combinatorial approach.
Counts orbits of nodes and edges from edge matrix or data frame, or a

Description: Functions to perform subspace clustering.

Description: Functions to perform subspace clustering and

Title: Subspace Clustering Based on Arbitrarily Oriented Projected
Description: Functions to perform subspace clustering and classification.
Packaged: 2018-03-17 16:22:58 UTC; szepannek

Title: Estimate procedure in case of first order autocorrelation
Author: Stefano Spada, Matteo Quartagno, Marco Tamburini
Description: This package has been implemented to solve first order
autocorrelation problems using an iterative method. This
procedure estimates both autocorrelation and beta coefficients
recursively until we reach the convergence (8th decimal). The
residuals are computed after estimating Beta using EGLS
approach and Rho is estimated using the previous residuals.

Title: Estimate Procedure in Case of First Order Autocorrelation
Authors@R: c(person("Stefano", "Spada", role = c("aut", "cre"), email = "lostefanospada@gmail.com"),
person("Matteo", "Quartagno", role = "ctb", email = "matteo.quartagno.lshtm.ac.uk"),
person("Marco", "Tamburini", role = "ctb"),
person("David", "Robinson", role = "ctb", email = "admiral.david@gmail.com"))
Description: Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.

Description: Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal as default). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.