* Optimal Designs for Copula Models* (

**docopulae**)

A direct approach to optimal designs for copula models based on the Fisher information. Provides flexible functions for building joint PDFs, evaluating the Fisher information and finding Ds-optimal designs. It includes an extensible solution to summation and integration called ‘nint’, functions for transforming, plotting and comparing designs, as well as a set of tools for common low-level tasks.

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**Ensemble of Subset of K-Nearest Neighbours Classifiers for Classification and Class Membership Probability Estimation****ESKNN**)

Functions for classification and group membership probability estimation are given. The issue of non-informative features in the data is addressed by utilizing the ensemble method. A few optimal models are selected in the ensemble from an initially large set of base k-nearest neighbours (KNN) models, generated on subset of features from the training data. A two stage assessment is applied in selection of optimal models for the ensemble in the training function. The prediction functions for classification and class membership probability estimation returns class outcomes and class membership probability estimates for the test data. The package includes measure of classification error and brier score, for classification and probability estimation tasks respectively.

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**Generate Short Unique YouTube-Like IDs (Hashes) from Integers****hashids**)

An R port of the hashids library. hashids generates YouTube-like hashes from integers or vector of integers. Hashes generated from integers are relatively short, unique and non-seqential. hashids can be used to generate unique ids for URLs and hide database row numbers from the user. By default hashids will avoid generating common English cursewords by preventing certain letters being next to each other. hashids are not one-way: it is easy to encode an integer to a hashid and decode a hashid back into an integer.

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**Neo4j Driver for R****RNeo4j**)

Neo4j, a graph database, allows users to store their data as a property graph. A graph consists of nodes that are connected by relationships; both nodes and relationships can have properties, or key-value pairs. RNeo4j is Neo4j’s R driver. It allows users to read and write data from and to Neo4j directly from their R environment by exposing an interface for interacting with nodes, relationships, paths, and more. Most notably, it allows users to retrieve Cypher query results as R data frames, where Cypher is Neo4j’s graph query language. Visit <http://www.neo4j.com> to learn more about Neo4j.

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**Analysis of Means****ANOM**)

Analysis of means (ANOM) as used in technometrical computing. The package takes results from multiple comparisons with the grand mean (obtained with multcomp, SimComp, nparcomp, or MCPAN) or corresponding simultaneous confidence intervals as input and produces ANOM decision charts that illustrate which group means deviate significantly from the grand mean.