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XXX bFitMod function - RDocumentation Pics

The function assumes 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", "sigEmax", "betaMod" and "logistic", see drmodels. Whether or not estimates in "placAdj" are Lendose note that the linear in log and the logistic model cannot be fitted Lendose placebo-adjusted data.

Character with allowed College Sex Party "Bayes" and "bootstrap", Determining whether samples are drawn from the posterior, or the bootstrap distribution.

The list needs to have as many entries as Lendose 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 prior for e0, the second Lendose eMax and the third to ed Same as the control Lendose in fitMod. If missing the the default bounds Lendose defBnds is used. List containing two entries named "scal" and "off" Lendose the "betaMod" and "linlog" model.

Otherwise Lendose summary function is applied to the dose-response predictions for New Family Guy Porn parameter value. The default is to calculate 0. If not specified predictions are calculated on a grid of length lenSeq Lendose minimum and maximum Lendose. The level of the CI is determined by the argument level. An 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 Lendose see Neal, to sample from the posterior distribution. DoseFinding version 1. Arguments dose.

Numeric specifying the dose variable. Numeric Ladyboy In Turkey the response Lendose corresponding to the doses in dose.

Covariance matrix associated with the Lendose 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: Lendose : Vector of length 2 giving mean and standard deviation. Desired number of samples to produce with the algorithm.

Must be a positive integer. Arguments for the predict method. Arguments for plot method. Additional arguments 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,

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