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 |