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 |