| averageResponse | Calculate the weighted average of estimated response values |
| bindModelResults | Bind results of one/several fitted model(s) into one summary... |
| bmr1 | Target function for optimization if ces.ans = 1 |
| bmr2 | Target function for optimization if ces.ans = 2 |
| bmr3 | Target function for optimization if ces.ans = 3 |
| bootstrapBmd | Estimate lower and upper bound for model-averaged bmd using... |
| calculateWeights | Calculate weights based on fitted models' aic |
| f.basics.cat | compute basic statistics of a categorical model |
| f.bb.bin | compute the value for parameter b, from values of other... |
| f.bb.cat | ? |
| f.bb.con | Determine value for parameter b for continuous response |
| f.boot.con | One bootstrap run for continuous response |
| f.cat | Main function for calculations with categorical response type |
| f.ced.cat | Determine values for the CED; categorical model |
| f.ced.con | Determine values for the CED; continuous response |
| f.cedlines.bin | Plot dotted lines for the determined CED value for... |
| f.cedlines.con | Plot dotted lines for the determined CED value for continous... |
| f.ced.pct | Calculate CI based on bootstrap estimates and confidence... |
| f.check.cc | Check whether the parameter value for c is too close to CES |
| f.check.nonneg.num | Check whether the data frame columns are numeric and can be... |
| f.CI | Wrapper function for calculating CI around parameter... |
| f.con | Main function for calculations with continuous response type |
| f.constr.con | Define lower and upper bounds for the model parameters;... |
| f.control | Define control parameters for nlminb(), which minimizes the... |
| f.converged | Determine convergence type of the minimization algorithm |
| f.dtype6.mn | Compare model fitted with and without alfa |
| f.execute | Calculate values for the response variable given the response... |
| f.expect.bin | Calculate expected response values, for categorical response |
| f.expect.cat | computed expected value for categorical model |
| f.expect.con | Calculate expected response values, for continuous response |
| f.hit.constr | Check whether any of the MLEs for the parameters hit the... |
| filterBestCovariates | Retain model with smallest AIC per family when considering... |
| findBestModel | Find the best model given a table of fitted models results |
| findBootstrapBounds | Find the lower and upper bound for bmd based on parametric... |
| f.ini | Define default parameter values needed in the proast... |
| f.inv.bin | return the CED value for a set of parameters, CES and ces.ans |
| f.inv.con | Determine value for the CED; continuous response |
| fitAllCovariates | Fit all covariate combinations for model parameters in given... |
| fitAllModels | Fit all model families for the continuous or quantal response |
| fitSingleModel | Fit single model for the continuous or quantal response |
| f.lik.cat | Calculate likelihood for categorical response |
| f.lik.con | Calculate likelihood for continuous response |
| f.lines.cat | plot lines for categorical model |
| f.lines.con | Plot the curve of the estimated model |
| f.lines.frq | Plot the lines |
| f.LL.bin | Calculate confidence intervals for each of the plotted points... |
| f.lump.cat | ? Add values to e.g. response y to avoid log of 0 |
| f.mm4.cat | Fit the model for a categorical response |
| f.mm4.con | Fit the model for a continuous response |
| f.mm6.cat | Calculate the CED values for a continuous response |
| f.mm6.con | Calculate the CED values for a continuous response |
| f.mm7.con | Main function for bootstrap method for calculating CI of CED |
| f.model.bb | change model.ans |
| f.nested.con | Calculations for nested factors (clustered response data) |
| f.nlminb | Minimization of the log-likelihood function |
| f.nr.gr | Determine the number of group ? |
| f.P | Calculate p-value for likelihood test |
| f.pars | Construct regression parameter matrix |
| f.pars.frq | ? |
| f.par.u | ? |
| f.plot.all | Wrapper function for plotting the results of proast |
| f.plot.con | Plot the predicted response values (points) and estimated CIs |
| f.plot.frq | Plot the predicted response values (points) and estimated CIs |
| f.proast | Main function to perform proast analysis |
| f.profile.all | Profile likelihood method to calculate confidence intervals |
| f.remove.NAs | Remove NAs from a given data frame for all listed column... |
| f.resid.con | Calculate residuals: difference of observed and expected... |
| f.scan | Load file in proast data format |
| f.split.par | split the vector of parameters |
| f.start.bin | Define initial parameter values for the chosen model, binary... |
| f.start.cat | Define initial parameter values for the chosen model,... |
| f.start.con | Define initial parameter values for the chosen model,... |
| f.start.lm.con | Fit linear model for continuous response |
| f.text.par | Define character vector with all parameter names |
| f.th.lvm | compute th.lvm? |
| f.uniroot.BMDratio | compute the root of the BMD ratio? |
| f.uniroot.probit | compute the value for the parameter b for a probit function |
| getModelNames | Index in Proast and full names of the fitted models |
| getModelParameters | Obtain the available model parameters for a given model... |
| makeForestPlot | Forest plot for estimated bmd, bmdl and bmdu values per... |
| matchWithResults | Find which fitted models' results match the listed model and... |
| optimizeBmd | Estimate the model-averaged BMD using numeric optimization... |
| pasteToVector | Paste elements of vector into string vector (for testing) |
| plotAverageModel | Plot for the model-averaged response values and bmd |
| printer | Print for debugging |
| runBmd | Run the BmdModeling Application |
| summaryModels | Summarize the results of all fitted models for continuous or... |
| testConstraints | Test function for defining parameter constraints |
| testCovariates | Test function for including covariates |
| testStartingValues | Test function for defining starting values |
