Since raw (survey) data usually has to be edited before statistical analysis can take place, the availability of data cleaning algorithms is important to many statisticians. In this paper the implementation of three data correction methods in R are described. The methods of this package can be used to correct numerical data under linear restrictions for typing errors, rounding errors, sign errors and value interchanges. The algorithms, based on earlier work of Scholtus, are described and implementation details with coded examples aregiven. Although the algorithms have originally been developed with financial balance accounts in mind the algorithms are formulated generically and can be applied in a wider range of applications.