Optimal Designs for Estimating the Slope Divided by the
Intercept
Adam Kapelner, Abba Krieger and William J. Blanford
Software which helps practitioners optimally design experiments
that measure the slope divided by the intercept (originally invented for HSGC
measurements) and provides confidence intervals. Other useful tools herein.

Compute optimal experimental designs
that measure the slope divided by the intercept.

Optimization Toolbox for solving linear systems
The optR function provides an option to solve the linear system
using numeric and non-meric approach. The current packages supports Gauss
Elimination, LU decomposition, Gauss-Sideil, and CGM methods to solve
equations having relationships of Ax=b form. The pacakge can be used to
build linear and non-linear models by defining them in linear system.

The optR function provides an option to solve the linear system
using numeric computation approach. The current packages supports Gauss
Elimination, LU decomposition, Gauss-Sideil, CGM and Cholesky methods to
solve equations having relationships of Ax=b form. The package can be used
to build linear and non-linear models by defining them in linear system.

Optimization Toolbox for Solving Linear Systems
Solves linear systems of form Ax=b via Gauss elimination,
LU decomposition, Gauss-Seidel, Conjugate Gradient Method (CGM) and Cholesky methods.

'surv' Object Confidence Bands Optimized by Area
Given a certain coverage level, obtains simultaneous confidence
bands for the survival and cumulative hazard functions such that the area
between is minimized. Produces an approximate solution based on local time
arguments.
stats, survival, km.ci, knitr, rmarkdown

Optimal Block Designs for Two-Colour cDNA Microarray Experiments
R (>= 3.3.1), MASS, Matrix, igraph, tcltk
Computes A-, MV-, D- and E-optimal or near-optimal block designs for two-colour cDNA microarray experiments using the linear fixed effects and mixed effects models where the interest is in a comparison of all possible elementary treatment contrasts. The algorithms used in this package are based on the treatment exchange and array exchange algorithms of Debusho, Gemechu and Haines (2016, unpublished). The package also provides an optional method of using the graphical user interface (GUI) R package tcltk to ensure that it is user friendly.