tinyErr: Remove observation, implementation, and process error

In DLMtool/DLMtool: Data-Limited Methods Toolkit

Description

Takes an existing OM object and converts it to one without any observation error, implementation error, very little process error, and/or gradients in life history parameters and catchability.

Usage

tinyErr(x, ...)

## S4 method for signature 'OM'
tinyErr(x, obs = TRUE, imp = TRUE, proc = TRUE, grad = TRUE, silent = FALSE)

Arguments

x	An object of class OM
...	Arguments to generic function
obs	Logical. Remove observation error? Obs is replaced with Perfect_Info
imp	Logical. Remove implementation error? Imp is replaced with Perfect_Imp
proc	Logical. Remove process error? All sd and cv slots in Stock and Fleet object are set to 0.
grad	Logical. Remove gradients? All grad slots in Stock and qinc in Fleet are set to 0.
silent	Logical. Display messages?

Details

Useful for debugging and testing that MPs perform as expected under perfect conditions.

Value

An updated object of class OM

Note

See relevant section of the DLMtool User Guide for more information.

Examples

OM_noErr <- tinyErr(DLMtool::testOM)

DLMtool/DLMtool documentation built on June 20, 2021, 5:20 p.m.