gaussplotR: Fit, Predict and Plot 2D-Gaussians in R

• Accepted by the Journal of Open Source Software

Post-peer review at the Journal of Open Source Software

• print() and summary() on objects that are output from fit_gaussian_2D() now round parameter estimates to two decimal places
• R version requirement downgraded to R >= 3.3.0

Update CRAN version to 0.2.3

Add autofit_gaussian_2D(), compare_gaussian_fits(), and characterize_gaussian_fits() to the CRAN version of the package. Minor updates elsewhere

add autofit, compare, and characterize functions

Newest functions enhance the automation of comparing among various Gaussian fit models. The autofit_gaussian_2D() function can be used to find the best-fitting model for a given data set. The compare_gaussian_fits() function compares models via criteria such as rmse or rss. A characterize_gaussian_fits() analyzes the orientation and partial correlations of Gaussian data. Features include computation of partial correlations between response variables and independent and diagonally-tuned predictions, along with Z-difference scoring.

Update CRAN to version 0.2.0

New features include fit_gaussian_2D(), which fits a 2D Gaussian to supplied data, along with updates to predict_gaussian_2D()

Add fit function

A function to fit 2D Gaussians to supplied data is now available; see gaussplotR::fit_gaussian_2D()

Add volume calculation

Added a compute_gaussian_volume() function to compute the volume under a given 2D gaussian

ready for CRAN submission

this release should take care of all the remaining issues re: CRAN submission

prep for CRAN submission

content of the package's functions has not changed; all recent updates were made to satisfy requirements for submitting to CRAN

ready for general use

The function predict_gaussian_2D() no longer requires a log2 transformation internally, which makes the function (and the package) more generically useful