# dtnorm: Truncated Normal Distribution In ggdmc: Cognitive Models

## Description

Random number generation, probability density and cumulative density functions for truncated normal distribution.

## Usage

 ```1 2 3 4 5``` ```dtnorm(x, mean, sd, lower, upper, log = FALSE) rtnorm(n, mean, sd, lower, upper) ptnorm(q, mean, sd, lower, upper, lt = TRUE, log = FALSE) ```

## Arguments

 `x, q` vector of quantiles; `mean` mean (must be scalar). `sd` standard deviation (must be scalar). `lower` lower truncation value (must be scalar). `upper` upper truncation value (must be scalar). `log` log probability. If TRUE (default is FALSE) probabilities p are given as `log(p)`. `n` number of observations. n must be a scalar. `lt` lower tail. If TRUE (default) probabilities are `P[X <= x]`, otherwise, `P[X > x]`.

a column vector.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```## rtn example dat1 <- rtnorm(1e5, 0, 1, 0, Inf) hist(dat1, breaks = "fd", freq = FALSE, xlab = "", main = "Truncated normal distributions") ## dtn example x <- seq(-5, 5, length.out = 1e3) dat1 <- dtnorm(x, 0, 1, -2, 2, 0) plot(x, dat1, type = "l", lwd = 2, xlab = "", ylab= "Density", main = "Truncated normal distributions") ## ptn example x <- seq(-50, 10, length.out = 1e3) mean <- 0 sd <- 1 lower <- 0 upper <- 5 dat1 <- ptnorm(x, 0, 1, 0, 5, log = TRUE) ```

ggdmc documentation built on Sept. 2, 2018, 1:03 a.m.