Check data against a datamodel
Read edits edits from free-form textfile
Names of edits
Parse textual, categorical edit rules to an editarray
Retrieve values stricktly implied by rules
Returns the constant part b of a linear (in)equality
Returns the derivation history of an edit matrix or array
Returns the operator part of a linear (in)equality editmatrix E
Determine edittypes in editset based on 'contains(E)'
Determine if a boolean matrix contains var
The errorLocation object
An overview of the function of package editrules
get seprator used to seperate variables from levels in editarray
Check for duplicate edit rules
Expand an edit expression
retrieve level names from editarray
Derive textual representation from (partial) indices
retrieve edit names from editarray
Returns augmented matrix representation of edit set.
Example editrules, used in vignette
Create an editmatrix
Get named logical array from editarray
get index list from editmatrix
Summarize data model of an editarray in a data.frame
Find obvious redundancies in set of edits
Check for obvious contradictions in a set of edits
Parse a categorical edit expression
Generate new errorlocation object
Returns the variable names of an (in)equality editmatrix E
editarray: logical array where every column corresponds to one
level of one variable. Every row is an edit. Every edit denotes
a *forbidden* combination.
Check which edits are dominated by other ones.
get variable names in editarray
parse categorial edit
print cateditmatrix
Normalizes an editmatrix
Workhorse function for localizeErrors
print editarray
Parse a numerical edit expression
Remove redundant dummy variables
Separate an editset into its disconnected blocks and simplify
Create an editmatrix object from its constituing attributes.
Read general edits
Eliminate a variable from a set of edit rules
Derive all essentially new implicit edits
Field code forest algorithm
Remove redundant variables and edits.
Create a backtracker object for error localization
Print violatedEdits
Parse a character vector of edits
Derive editmatrix with soft constraints. This is a utility function that is used for
constructing a mip/lp problem.
print a backtracker
Localize errors using a MIP approach.
Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for
constructing a mip/lp problem.
Returns the variable names of an (in)equality editmatrix E
get variable names
Parse a mixed edit
Print object of class errorLocation
Get upperbounds of edits, given the boundaries of all variables
summary
Rewrite an editset and reported values into the components needed for a mip solver
get names of variables in a set of edits
Check if an editmatrix is normalized
Check consistency of set of edits
Localize errors on records in a data.frame.
Check object class
Compute index from array part of editarray
Number of edits
Count the number of edits in a collection of edits.
Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for
constructing a mip/lp problem.
Row index operator for editmatrix
summary
print editset
print editmatrix
print editset
Simplify logical mixed edits in an editset
Replace a variable by a value in a set of edits.
Derive editmatrix with soft constraints based on boundaries of variables. This is a utility function that is used for
constructing a mip/lp problem.
Check data against constraints
Coerce a matrix to an edit matrix.
as.character.cateditmatrix
Coerce an cateditmatrix to a character vector
Backtracker: a flexible and generic binary search program
Add dummy variable to the data.frames, these are needed for errorlocations etc.
Coerce x to an editset
Write an editset into a mip representation
Coerces a mip object into an lpsolve object
Transform a found solution into a categorical record
Decouple a set of conditional edits
Decompose a matrix or edits into independent blocks
Get condition matrix from an editset.
Determine which edits contain which variable(s)
Returns the coefficient matrix A of linear (in)equalities
Derive adjecency matrix from collection of edits
Check for duplicate edit rules
Graphical representation of edits
Bring an (edit) matrix to reduced row echelon form.
Create an editmatrix with categorical variables