addResids | Add residuals by adding to mean effects |

backscaleResids | Backscale residuals |

Blissindependence | Bliss Independence Model |

bootConfInt | Obtain confidence intervals for the raw effect sizes on every off-axis point and overall |

boxcox.transformation | Apply two-parameter Box-Cox transformation |

coef.MarginalFit | Coefficients from marginal model estimation |

col2hex | R color to RGB (red/green/blue) conversion. |

constructFormula | Construct a model formula from parameter constraint matrix |

contour.ResponseSurface | Method for plotting of contours based on maxR statistics |

df.residual.MarginalFit | Residual degrees of freedom in marginal model estimation |

directAntivirals | Partial data with combination experiments of direct-acting antivirals |

directAntivirals_ALL | Full data with combination experiments of direct-acting antivirals |

fitMarginals | Fit two 4-parameter log-logistic functions for a synergy experiment |

fitSurface | Fit response surface model and compute meanR and maxR statistics |

fitted.MarginalFit | Compute fitted values from monotherapy estimation |

fitted.ResponseSurface | Predicted values of the response surface according to the given null model |

generalizedLoewe | Compute combined predicted response from drug doses according to standard or generalized Loewe model. |

generateData | Generate data from parameters of marginal monotherapy model |

get.abs_tval | Return absolute t-value, used in optimization call in 'optim.boxcox' |

get.summ.data | Summarize data by factor |

getCP | Estimate CP matrix from bootstraps |

getd1d2 | A function to get the d1d2 identifier |

getR | Helper functions for the test statistics |

GetStartGuess | Estimate initial values for dose-response curve fit |

getTransformations | Return a list with transformation functions |

harbronLoewe | Alternative Loewe generalization |

hsa | Highest Single Agent model |

initialMarginal | Estimate initial values for fitting marginal dose-response curves |

isobologram | Isobologram of the response surface predicted by the null model |

L4 | 4-parameter logistic dose-response function |

marginalNLS | Fit two 4-parameter log-logistic functions with non-linear least squares |

marginalOptim | Fit two 4-parameter log-logistic functions with common baseline |

maxR | Compute maxR statistic for each off-axis dose combination |

meanR | Compute meanR statistic for the estimated model |

modelVar | Calculate model variance, assuming variance increases linearly with mean |

optim.boxcox | Find optimal Box-Cox transformation parameters |

outsidePoints | List non-additive points |

plot.BIGLconfInt | Plot confidence intervals in a contour plot |

plot.effect-size | Plot of effect-size object |

plot.MarginalFit | Plot monotherapy curve estimates |

plot.maxR | Plot of maxR object |

plot.meanR | Plot bootstrapped cumulative distribution function of meanR null distribution |

plot.ResponseSurface | Method for plotting response surface objects |

plotConfInt | Plot confidence intervals from BIGL object in a contour plot |

plotMeanVarFit | Make a mean-variance plot |

plotResponseSurface | Plot response surface |

predict.MarginalFit | Predict values on the dose-response curve |

predictOffAxis | Compute off-axis predictions |

predictResponseSurface | Predict the entire response surface, so including on-axis points, and return the result as a matrix. For plotting purposes. |

predictVar | Predict variance |

print.summary.BIGLconfInt | Print summary of BIGLconfInt object |

print.summary.MarginalFit | Print method for summary of 'MarginalFit' object |

print.summary.maxR | Print summary of maxR object |

print.summary.meanR | Print summary of meanR object |

print.summary.ResponseSurface | Print method for the summary function of 'ResponseSurface' object |

residuals.MarginalFit | Residuals from marginal model estimation |

runBIGL | Run the BIGL application for demonstrating response surfaces |

sampleResids | Sample residuals according to a new model |

scaleResids | Functions for scaling, and rescaling residuals. May lead to unstable behaviour in practice |

simulateNull | Simulate data from a given null model and monotherapy coefficients |

summary.BIGLconfInt | Summary of confidence intervals object |

summary.MarginalFit | Summary of 'MarginalFit' object |

summary.maxR | Summary of maxR object |

summary.meanR | Summary of meanR object |

summary.ResponseSurface | Summary of 'ResponseSurface' object |

synergy_plot_bycomp | Plot 2D cross section of response surface |

vcov.MarginalFit | Estimate of coefficient variance-covariance matrix |

wildbootAddResids | Sample residuals according to a new model |