Multiple.resp.surface.fit: Multiple.resp.surface.fit

In Michorlab/ACESO: A Cancer Evolution Simulation Optimizer

Description

Fits a generalized additive model (gam) or a polynomial surface (loess) to data of multiple cell lines.

Usage

Multiple.resp.surface.fit(data, resp = "Birth_rate", conc1 = "CONC",
  conc2 = "CONC2", Drug1.name = "Drug 1", Drug2.name = "Drug 2",
  logscale = T, method = c("gam", "loess"), title = "")

Arguments

data	Concentration-effect dataframe.
resp	Name of the column with the response values. Default is Birth_rate.
conc1	Name of the column with the concentration values for drug 1.
conc2	Name of the column with the concentration values for drug 2.
Drug1.name	string to specify the name of drug 1.
Drug2.name	string to specify the name of drug 2.
logscale	determines whether the input variables will be plotted on a logarithmic scale, or a standard linear scale. Because this function is intended primarily for visualizing combined action dose-response, a logarithmic dose-pair space is the default.
method	array to specify if a generalized additive model (gam) or a polynomial surface (loess) model must be fitted to the data.
title	title for the drug.

Value

This function returns a fitted gam object (see gamObject for a detailed description) or an object of class "loess".

See Also

gamObject

Examples

## Not run: 
data(Dactolisib_Trametinib_rates)
gam.model=Multiple.resp.surface.fit(GD,resp='Birth_rate',conc1='CONC',conc2='CONC2', 
title=", GAM with raw data")
print(gam.model)

## End(Not run)

Michorlab/ACESO documentation built on June 4, 2021, 4:57 p.m.