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Access to Fragile Families Metadata
A collection of functions that allows users to retrieve metadata for the Fragile Families challenge via a Web API (< http://api.metadata.fragilefamilies.princeton.edu>). Users can select and search metadata for relevant variables by filtering on different attribute names.
Compute Neural Fragility for Ictal iEEG Time Series
Provides tools to compute the neural fragility matrix from intracranial electrocorticographic (iEEG) recordings, enabling the analysis of brain dynamics during seizures. The package implements the method described by Li et al. (2017)
Clock of Regimes for Regime-Switching Fragility Analysis
Implements the Clock of Regimes (KRONX) framework for regime-switching fragility analysis of financial time series. The package fits Gaussian and Student-t Hidden Markov Models (HMMs) to return data, constructs a hazard-adjusted transition operator Q, derives the associated generator K = Q - I, and computes the fundamental matrix N = -K inverse to characterize expected residence times under structural fragility.
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.
Flexible Procedures for Clustering
Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.
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,
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.
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.
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.
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'.