N-Parameter Logistic Regression

Performing drug response analyses and IC50 estimations using n-Parameter logistic regression. Can also be applied to proliferation analyses.

The nplr package is currently in development and is not yet available via CRAN. To install a test version of the package, use devtools:



R News

nplr package 0.1-7

SIGNIFICANT USER-VISIBLE CHANGES * Both GOF and weighted GOF are computed. They are returned in the model summary and can be displayed in the plot. See vignette for details.

nplr package 0.1-6

SIGNIFICANT USER-VISIBLE CHANGES * A getWeights() function is added, which returns both the weighted and non-weighted standard errors.

BUG FIXES * Error in std-error (weighted and non-weighted) computation, fixed.

nplr package 0.1-5

SIGNIFICANT USER-VISIBLE CHANGES * A nplr-class summary is added.

nplr package 0.1-4

SIGNIFICANT USER-VISIBLE CHANGES * New example file 'multiplecell.tsv' containing multiple experiment results. * New graphical options in overlay(): showLegend, Cols. * Updated vignette with nplrApp presentation

nplr package 0.1-3

SIGNIFICANT USER-VISIBLE CHANGES * Simplified plot() function with less predifined graphical parameters.

NEW FEATURES * New overlay() function to superimpose multiple curves.

nplr package 0.1-2

SIGNIFICANT USER-VISIBLE CHANGES * New method for estimating the weighted Goodness-of-Fit

nplr package 0.1-1: First release!


NEW FEATURES * New package

BUG FIXES * No changes classified as 'bug fixes' (package under active development)

Reference manual

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0.1-7 by Frederic Commo, 2 years ago


Browse source code at https://github.com/cran/nplr

Authors: Frederic Commo [aut, cre] , Brian M. Bot [aut]

Documentation:   PDF Manual  

GPL license

Imports stats, graphics, utils

Depends on methods

Suggests RUnit, knitr

See at CRAN