methods, parallel, GA (>= 3.1.1), snow, doSNOW, iterators,
pso, ucminf, foreach, graphics, optimParallel

Evaluate binary classificaton models produced by the EigenDog web-service.

Evaluate binary classification models produced by the
EigenDog web-service.

Generates (dense) matrices that have a given set of eigenvalues
Solves the ``inverse eigenvalue problem'' which is to
generate a real-valued matrix that has the specified real
eigenvalue spectrum.  It can generate infinitely many dense
matrices, symmetric or asymmetric, with the given set of
eigenvalues.  Algorithm can also generate stochastic and doubly
stochastic matrices.

Semiparametric factor and regression models for symmetric
relational data
This package estimates the parameters of a model for
symmetric relational data (e.g., the above-diagonal part of a
square matrix), using a model-based eigenvalue decomposition
and regression. Missing data is accomodated, and a posterior
mean for missing data is calculated under the assumption that
the data are missing at random. The marginal distribution of
the relational data can be arbitrary, and is fit with an
ordered probit specification.

Semiparametric Factor and Regression Models for Symmetric
Relational Data
Estimation of the parameters in a model for
symmetric relational data (e.g., the above-diagonal part of a
square matrix), using a model-based eigenvalue decomposition
and regression. Missing data is accommodated, and a posterior
mean for missing data is calculated under the assumption that
the data are missing at random. The marginal distribution of
the relational data can be arbitrary, and is fit with an
ordered probit specification. See Hoff (2007) <arXiv:0711.1146>
for details on the model.

Computes confidence intervals for principal components
Computes confidence intervals for the proportion explained by the first 1,2,k principal components, and computes confidence intervals for each eigenvalue. Both computations are done via nonparametric bootstrap.

c(person(given = "Wayne", family = "Oldford",
email = "rwoldford@uwaterloo.ca",
role = c("aut", "cre")),
person(given = "Erle", family = "Holgersen",
email = "emholgersen@uwaterloo.ca",
role = "aut"),
person(given = "Ben", family = "Lafreniere",
email = "ben.lafreniere@gmail.com",
role = "aut"),
person(given = "Tianlu", family = "Zhu",
email = "t8zhu@uwaterloo.ca",
role = "aut")
)
Wayne Oldford [aut, cre],
Erle Holgersen [aut],
Ben Lafreniere [aut],
Tianlu Zhu [aut]