Skip to content

GitLab

  • Menu
Projects Groups Snippets
    • Loading...
  • Help
    • Help
    • Support
    • Community forum
    • Submit feedback
    • Contribute to GitLab
  • Sign in / Register
  • airGR airGR
  • Project information
    • Project information
    • Activity
    • Labels
    • Members
  • Repository
    • Repository
    • Files
    • Commits
    • Branches
    • Tags
    • Contributors
    • Graph
    • Compare
  • Issues 60
    • Issues 60
    • List
    • Boards
    • Service Desk
    • Milestones
  • Redmine
    • Redmine
  • Merge requests 7
    • Merge requests 7
  • CI/CD
    • CI/CD
    • Pipelines
    • Jobs
    • Schedules
  • Deployments
    • Deployments
    • Environments
    • Releases
  • Monitor
    • Monitor
    • Incidents
  • Packages & Registries
    • Packages & Registries
    • Container Registry
  • Analytics
    • Analytics
    • Value stream
    • CI/CD
    • Repository
  • Wiki
    • Wiki
  • Snippets
    • Snippets
  • Activity
  • Graph
  • Create a new issue
  • Jobs
  • Commits
  • Issue Boards
Collapse sidebar
  • HYCAR-Hydro
  • airGRairGR
  • Issues
  • #19

Closed
Open
Created Nov 20, 2019 by Thirel Guillaume@guillaume.thirelOwner

Several issues on the BoxCox transformation calculation

It appears that there are several mistakes in the case the boxcox calculation is used in .ErrorCrit.

First, an epsilon is added to Qobs and Qsim although it is not necessary for BoxCox:

  if ("epsilon" %in% names(InputsCrit) & !is.null(InputsCrit$epsilon)) {
    VarObs <- VarObs + InputsCrit$epsilon
    VarSim <- VarSim + InputsCrit$epsilon
  }

should become

  if ("epsilon" %in% names(InputsCrit) & !is.null(InputsCrit$epsilon) & !(InputsCrit$transfo == "boxcox")) {
    VarObs <- VarObs + InputsCrit$epsilon
    VarSim <- VarSim + InputsCrit$epsilon
  }

Then, the formula is wrong:

    VarSim <- (VarSim^0.25 - 0.01 * mean(VarSim, na.rm = TRUE)) / 0.25
    VarObs <- (VarObs^0.25 - 0.01 * mean(VarObs, na.rm = TRUE)) / 0.25

should be replaced with

    VarSim <- (VarSim^0.25 – (0.01 * mean(VarObs, na.rm = TRUE))^0.25 ) / 0.25
    VarObs <- (VarObs^0.25 – (0.01 * mean(VarObs, na.rm = TRUE))^0.25 ) / 0.25
Assignee
Assign to
Time tracking