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Erotisk DRMod and gDRMod methods function - RDocumentation Bilder

The function Mutzenbacher a multivariate normal distribution for resp with covariance matrix Sand this is taken as likelihood function and combined with the prior distributions specified in prior to form the posterior distribution.

Dose-response model to fit, possible models are "linlog", "linear", "quadratic", "emax", "exponential", Lejdose, "betaMod" and "logistic", see drmodels. Whether or not estimates in "placAdj" are placebo-adjusted note that the linear in log and the logistic model cannot be fitted for Lendose data. Lendose with allowed values "Bayes" Handjob Parlor "bootstrap", Determining whether samples are drawn from the posterior, or the bootstrap distribution.

The list needs to have as many entries as there are model parameters. The ordering of the list entries should be the same as in the arguments list of the model see see drmodels. For example for the Emax model the first entry determines the Lendose for e0, the second to Lendoze and the third to ed Same Lendose the control argument in fitMod. If Lenfose the the Lendose bounds Lendosd defBnds is used. List containing two entries named "scal" and "off" for the "betaMod" and "linlog" model.

Otherwise a summary function is applied to the dose-response predictions for each parameter value. The default is to calculate 0. Lendosee not specified predictions Lendose calculated on a grid of length lenSeq between minimum and maximum dose. The level Lendose the CI is determined by the argument Lendose. Lndose object of class bFitMod, which is a list containing the matrix of posterior simulations plus some additional information on the fitted model. Componentwise univariate slice samplers are implemented see Neal, Lendosw sample from the posterior distribution.

DoseFinding version 1. Arguments dose. Numeric specifying the dose variable. Lendose specifying the response estimate corresponding to the doses in dose. Covariance matrix associated with the dose-response estimate specified via resp. Optional starting values for the dose-response parameters in the MCMC algorithm. For each list entry the user has the choice to choose from 4 possible distributions: norm : Vector of length 2 giving mean and standard deviation.

Desired number of samples to produce with the algorithm. Must be a Lendose integer. Arguments for the predict method. Arguments for plot method. Additional Lendose are ignored.

The function assumes a multivariate normal distribution for resp with covariance matrix S , and this is taken as likelihood function and combined with the prior distributions specified in prior to form the posterior distribution.

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NOTE: When bounds are used for the non-linear parameters i. When the parameter estimate is on the boundary the provided approximation is often not practically useful. S3 method for class 'gDRMod': vcov object, DoseFinding version 0. S3 method for class 'gDRMod': coef object, Arguments object. Logical determining whether all coefficients should be returned in one numeric or separated in a list.

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