ptnorm: Distribution function truncated normal

In BNPdensity: Ferguson-Klass Type Algorithm for Posterior Normalized Random Measures

Distribution function truncated normal

Description

Computes the cumulative distribution function.

Usage

ptnorm(
  q,
  mean = 0,
  sd = 1,
  lower = -Inf,
  upper = Inf,
  lower.tail = TRUE,
  log.p = FALSE
)

Details

For internal use

Note

Taken from msm R-package.

Author(s)

C. H. Jackson

References

Taken from

Examples

## The function is currently defined as
function(q, mean = 0, sd = 1, lower = -Inf, upper = Inf, lower.tail = TRUE,
         log.p = FALSE) {
  ret <- numeric(length(q))
  if (lower.tail) {
    ret[q < lower] <- 0
    ret[q > upper] <- 1
  }
  else {
    ret[q < lower] <- 1
    ret[q > upper] <- 0
  }
  ret[upper < lower] <- NaN
  ind <- q >= lower & q <= upper
  if (any(ind)) {
    denom <- pnorm(upper, mean, sd) - pnorm(
      lower, mean,
      sd
    )
    if (lower.tail) {
      qtmp <- pnorm(q, mean, sd) - pnorm(lower, mean, sd)
    } else {
      qtmp <- pnorm(upper, mean, sd) - pnorm(
        q, mean,
        sd
      )
    }
    if (log.p) {
      qtmp <- log(qtmp) - log(denom)
    } else {
      qtmp <- qtmp / denom
    }
    ret[q >= lower & q <= upper] <- qtmp[ind]
  }
  ret
}

BNPdensity documentation built on April 1, 2023, 12:10 a.m.