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Easy to use interfaces to a number of imputation methods that fit in the not-a-pipe operator of the 'magrittr' package.
Hash R Objects to Integers Fast
Apply the SuperFastHash algorithm to any R object. Hash whole R objects or, for vectors or lists, hash R objects to obtain a set of hash values that is stored in a structure equivalent to the input.
Data Correction and Imputation Using Deductive Methods
Attempt to repair inconsistencies and missing values in data records by using information from valid values and validation rules restricting the data.
Modify Data Using Externally Defined Modification Rules
Data cleaning scripts typically contain a lot of 'if this change that' type of statements. Such statements are typically condensed expert knowledge. With this package, such 'data modifying rules' are taken out of the code and become in stead parameters to the work flow. This allows one to maintain, document, and reason about data modification rules as separate entities.
Useful functions for visual word recognition research
Functions and data for use in visual word recognition research: Computation of neighbors (Hamming and Levenshtein distances), average distances to neighbors (e.g., OLD20), and Coltheart's N. Also includes the LD1NN algorithm to detect bias in the composition of a lexical decision task. Most of the functions support parallel execution. Supplies wordlists for several languages. Uses the string distance functions from the stringdist package by Mark van der Loo.
Locate Errors with Validation Rules
Errors in data can be located and removed using validation rules from package 'validate'.
Trends and Indices for Monitoring Data
The TRIM model is widely used for estimating growth and decline of animal populations based on (possibly sparsely available) count data. The current package is a reimplementation of the original TRIM software developed at Statistics Netherlands by Jeroen Pannekoek. See < https://www.cbs.nl/en-gb/society/nature-and-environment/indices-and-trends%2d%2dtrim%2d%2d> for more information about TRIM.
Extending 'dendrogram' Functionality in R
Offers a set of functions for extending 'dendrogram' objects in R, letting you visualize and compare trees of 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different 'dendrograms' to one another.
Checking and Simplifying Validation Rule Sets
Rule sets with validation rules may contain redundancies or contradictions. Functions for finding redundancies and problematic rules are provided, given a set a rules formulated with 'validate'.
Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models
Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.