Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 51 packages in 0.07 seconds

matman — by Leon Binder, 2 months ago

Material Management

A set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.

rbch — by Rucknium, 2 years ago

Extraction and Analysis of Data from the Bitcoin Cash (BCH) Blockchain

Issues RPC-JSON calls to 'bitcoind', the daemon of Bitcoin Cash (BCH), to extract transaction data from the blockchain. BCH is a fork of Bitcoin that permits a greater number of transactions per second. A BCH daemon is available under an MIT license from the Bitcoin Unlimited website < https://www.bitcoinunlimited.info>.

treePlotArea — by Andreas Dominik Cullmann, 4 months ago

Correction Factors for Tree Plot Areas Intersected by Stand Boundaries

The German national forest inventory uses angle count sampling, a sampling method first published as `Bitterlich, W.: Die Winkelzählmessung. Allgemeine Forst- und Holzwirtschaftliche Zeitung, 58. Jahrg., Folge 11/12 vom Juni 1947` and extended by Grosenbaugh (< https://academic.oup.com/jof/article-abstract/50/1/32/4684174>) as probability proportional to size sampling. When plots are located near stand boundaries, their sizes and hence their probabilities need to be corrected.

rBDAT — by Christian Vonderach, 10 months ago

Implementation of BDAT Tree Taper Fortran Functions

Implementing the BDAT tree taper Fortran routines, which were developed for the German National Forest Inventory (NFI), to calculate diameters, volume, assortments, double bark thickness and biomass for different tree species based on tree characteristics and sorting information. See Kublin (2003) for details.

parma — by Alexios Galanos, 3 years ago

Portfolio Allocation and Risk Management Applications

Provision of a set of models and methods for use in the allocation and management of capital in financial portfolios.

vostokR — by Andrew J. Sanchez Meador, 8 days ago

Solar Potential Calculation for Point Clouds using 'VOSTOK'

Calculate solar potential for LiDAR point clouds using the 'VOSTOK' (Voxel Octree Solar Toolkit) algorithm. This R program provides an interface to the original 'VOSTOK' C++ implementation by Bechtold and Hofle (2020), enabling efficient ray casting and solar position algorithms to compute solar irradiance for each point while accounting for shadowing effects. Integrates seamlessly with the 'lidR' package for LiDAR data processing workflows. The original 'VOSTOK' toolkit is available at .

nlsem — by Nora Umbach, 3 years ago

Fitting Structural Equation Mixture Models

Estimation of structural equation models with nonlinear effects and underlying nonnormal distributions.

holland — by Joerg-Henrik Heine, 7 months ago

Statistics for Holland's Theory of Vocational Choice

Offers a convenient way to compute parameters in the framework of the theory of vocational choice introduced by J.L. Holland, (1997). A comprehensive summary to this theory of vocational choice is given in Holland, J.L. (1997). Making vocational choices. A theory of vocational personalities and work environments. Lutz, FL: Psychological Assessment.

svars — by Alexander Lange, 7 months ago

Data-Driven Identification of SVAR Models

Implements data-driven identification methods for structural vector autoregressive (SVAR) models as described in Lange et al. (2021) . Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) ), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) ), independent component analysis (Matteson, D. S, Tsay, R. S., (2013) ), least dependent innovations (Herwartz, H., Ploedt, M., (2016) ), smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) ) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) )).

streamMOA — by Michael Hahsler, 2 years ago

Interface for MOA Stream Clustering Algorithms

Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework (Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer (2010). MOA: Massive Online Analysis, Journal of Machine Learning Research 11: 1601-1604).