expect_equal | expect_equivalent | expect_identical | expect_null | expect_true, expect_false | expect_message | expect_warning | expect_error | expect_silent | ignore

Preface | Prerequisites | Citing this work | Acknowledgements | Contributing | License | Introduction to validate | A quick example | Variable checks | Variable type | Missingness | Field length | Format of numeric fields | General field format | Numeric ranges | Ranges for times and periods | Code lists | Availability and uniqueness | Long data | Uniqueness | Availability of records | Gaps in (time) series | Multivariate checks | Completeness of records | Balance equalities and inequalities | Conditional restrictions | Forbidden value combinations | Statistical checks | Statistical and groupwise characteristics | Group properties | Code hierarchies and aggregation | General aggregates in long-form data | Notes | Aggregates of time series in long format | Indicators | A first example | Getting indicator values | Working with validate | Manipulating rule sets | Rule metadata | Rules in data frames | Validation rule syntax | Confrontation objects | Confrontation options | Using reference data | Rules in text files | Reading rules from file | Metadata in text files: YAML | Setting options | Including other rule files | Exporting validator objects | Rules from SDMX | SDMX and validate | SDMX and API locations | Code lists from SDMX registries | Derive rules from DSD | More on SDMX | Comparing data sets | Cell counts | Comparing rule violations | validate and lumberjack | Bibliographical notes

title: Introduction to accumulateauthor: Mark P.J. van der Loocss: "style.css" | Introduction | Installation | A first example | Exercises | The formula interface for specifying collapsing schemes | The data frame interface for defining collapsing schemes | Convenience functions to define tests | Complex aggregates | Smoke-testing your test function

title: Introduction to synthesizerauthor: Mark P.J. van der Loocss: style.css | Introduction | Installation | A first example | Controlling the utility-privacy trade-off | Synthesizing (multivariate) time series | How it works

title: Introduction to dcmodifyauthor: Mark P.J. van der Loo and Edwin de Jongecss: "style.css" | Introduction | Example | What's the idea | Exercises | Import/export of rules and rule metadata | Exercise | Using reference data | Supported rules | Tracking changes | References

Purpose of this package: unit testing | Expressing tests | Test files | Testing packages | Testing with environmental variables | Running tests in parallel | A few tips on packages and unit testing

Installation | General remarks | A first example | Chaining imputation methods | Similar model for multiple variables | Grouping data for imputation | Specify your own method with impute_proxy | Imputing a dataset with models trained on another dataset | Using VIM as (much) faster backend for hotdeck imputations

Purpose of this package: tracking changes in data | Tracking changes in scripts that process data | A little background | Controlling where the logging data is written | Tracking multiple datasets | Tracking changes in data in interactive sessions | Available loggers | Properties of the lumberjack pipe operator | Extending lumberjack

Gower's distance measure | Computing Gower's distance | Computing the top-n best matches | Using weights | Parallelization, memory usage

What are options? | What does the settings package do? | Basic option settings management | Limiting options | Global versus local options | Using the settings package as options manager for your package. | An example S4 class with local options and global default | An example Reference class with local options and global default

Example 1: hard-coded checks | Check function API | Example 2: general checkers | Exercises

Introduction | Example | Optimization in R | Sparse problems | Reusing sparsely defined restrictions | References | Some words on the rspa package