# paramtnormci_numeric: Return parameters of truncated normal distribution based on a... In decisionSupport: Quantitative Support of Decision Making under Uncertainty

## Description

This function calculates the distribution parameters, i.e. `mean` and `sd`, of a truncated normal distribution from an arbitrary confidence interval.

## Usage

 ```1 2``` ```paramtnormci_numeric(p, ci, lowerTrunc = -Inf, upperTrunc = Inf, relativeTolerance = 0.05, rootMethod = "probability", ...) ```

## Arguments

 `p` `numeric` 2-dimensional vector; probabilities of lower and upper bound of the corresponding confidence interval. `ci` `numeric` 2-dimensional vector; lower, i.e `ci[[1]]`, and upper bound, i.e `ci[[2]]`, of the confidence interval. `lowerTrunc` `numeric`; lower truncation point of the distribution (>= `-Inf`). `upperTrunc` `numeric`; upper truncation point of the distribution (<= `Inf`). `relativeTolerance` `numeric`; the relative tolerance level of deviation of the generated confidence interval from the specified interval. If this deviation is greater than `relativeTolerance` a warning is given. `rootMethod` `character`; if `="probability"` the equation defining the parameters `mean` and `sd` is the difference between calculated and given probabilities of the confidence interval; if `="quantile"` the equation defining the parameters is the difference between calculated and given upper and lower value of the confidence interval. `...` Further parameters passed to `nleqslv`.

## Details

For details of the truncated normal distribution see `tnorm`. #' @importFrom nleqslv nleqslv

## Value

A list with elements `mean` and `sd`, i.e. the parameters of the underlying normal distribution.

`tnorm`, `nleqslv`