# pdist: Helper function that gives the probability distribution... In indirect: Elicitation of Independent Conditional Means Priors for Generalised Linear Models

## Description

Helper function that gives the probability distribution function for design point.

## Usage

 `1` ```pdist(x, Z, design.pt = NULL, fit.method = "KL") ```

## Arguments

 `x` numeric: coordinate `Z` list of design points and link function, see `designLink` `design.pt` integer: design point `fit.method` character: method for fit in `mV`, default is `KL`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```# design matrix: two scenarios X <- matrix(c(1, 1, 0, 1), nrow = 2) rownames(X) <- c("scenario1", "scenario2") colnames(X) <- c("covariate1", "covariate2") #' # logit link # central credible intervals with probability = 1/2 Z <- designLink(design = X, link = "logit", CI.prob = 0.5) #' # lower and upper quartiles and median Z <- indirect::elicitPt(Z, design.pt = 1, lower.CI.bound = 0.2, median = 0.4, upper.CI.bound = 0.6, comment = "Completed.") indirect::plotDesignPoint(Z, design.pt = 1, elicited.fractiles = TRUE, theta.bounds = c(0, 1), fitted.fractiles = TRUE, fitted.curve = TRUE) # probability that target is below 0.1 and # probability that target is below 0.9 indirect::pdist(c(0.1, 0.9), Z, design.pt = 1) ```

indirect documentation built on May 1, 2019, 6:35 p.m.