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Process Based Epidemiological Model for Cercospora Leaf Spot of Sugar Beet
Estimates sugar beet canopy closure with remotely sensed leaf area index and estimates when action might be needed to protect the crop from a Leaf Spot epidemic with a negative prognosis model based on published models.
Generalized Price and Quantity Indexes
Tools to build and work with bilateral generalized-mean
price indexes (and by extension quantity indexes), and indexes composed of
generalized-mean indexes (e.g., superlative quadratic-mean indexes, GEKS).
Covers the core mathematical machinery for making bilateral price indexes,
computing price relatives, detecting outliers, and decomposing indexes,
with wrappers for all common (and many uncommon) index-number
formulas. Implements and extends many of the methods in
Balk (2008,
Convex Clustering Methods and Clustering Indexes
Convex Clustering methods, including K-means algorithm, On-line Update algorithm (Hard Competitive Learning) and Neural Gas algorithm (Soft Competitive Learning), and calculation of several indexes for finding the number of clusters in a data set.
Random Cluster Generation (with Specified Degree of Separation)
We developed the clusterGeneration package to provide functions for generating random clusters, generating random covariance/correlation matrices, calculating a separation index (data and population version) for pairs of clusters or cluster distributions, and 1-D and 2-D projection plots to visualize clusters. The package also contains a function to generate random clusters based on factorial designs with factors such as degree of separation, number of clusters, number of variables, number of noisy variables.
Statistical Procedures for Agricultural Research
Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.
Fast and Simple 'MongoDB' Client for R
High-performance MongoDB client based on 'mongo-c-driver' and 'jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. The online user manual provides an overview of the available methods in the package: < https://jeroen.github.io/mongolite/>.
Hexagonal Hierarchical Geospatial Indexing System
Provides access to Uber's 'H3' geospatial indexing system via 'h3lib' < https://CRAN.R-project.org/package=h3lib>. 'h3r' is designed to mimic the 'H3' Application Programming Interface (API) < https://h3geo.org/docs/api/indexing/>, so that any function in the API is also available in 'h3r'.
Classes and Methods for Fast Memory-Efficient Boolean Selections
Provided are classes for boolean and skewed boolean vectors, fast boolean methods, fast unique and non-unique integer sorting, fast set operations on sorted and unsorted sets of integers, and foundations for ff (range index, compression, chunked processing).
Validation of Clustering Results
Statistical and biological validation of clustering results. This package implements Dunn Index, Silhouette, Connectivity, Stability, BHI and BSI. Further information can be found in Brock, G et al. (2008)
Quick Indexation
Quick indexation of any type of vector or of any combination of those. Indexation turns a vector into an integer vector going from 1 to the number of unique elements. Indexes are important building blocks for many algorithms. The method is described at < https://github.com/lrberge/indexthis/>.