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Estimate the Probability in the Upper Tail of the Aggregate Loss Distribution

Set of tools to estimate the probability in the upper tail of the aggregate loss distribution using different methods: Panjer recursion, Monte Carlo simulations, Markov bound, Cantelli bound, Moment bound, and Chernoff bound.

Latent Variable Models for Networks

Latent variable models for network data using fast inferential procedures. For more information please visit: < http://igollini.github.io/lvm4net/>.

Geographically-Weighted Models

Techniques from a particular branch of spatial statistics,termed geographically-weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. 'GWmodel' includes functions to calibrate: GW summary statistics (Brunsdon et al., 2002)

A Vincent Van Gogh Color Palette Generator

Palettes generated from Vincent van Gogh's paintings.

Disaggregate Variable Costs

These functions were developed within SECFISH project (Strengthening regional cooperation in the area of fisheries data collection-Socio-economic data collection for fisheries, aquaculture and the processing industry at EU level). They are aimed at identifying correlations between costs and transversal variables by metier using individual vessel data and for disaggregating variable costs from fleet segment to metier level.

Tools for Single Cell Genomics

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015)

Indices for Single-Case Research

Parametric and nonparametric statistics for single-case design. Regarding nonparametric statistics, the index suggested by Parker, Vannest, Davis and Sauber (2011)

Collection of Machine Learning Datasets for Supervised Machine Learning

Contains a collection of datasets for working with machine learning tasks.
It will contain datasets for supervised machine learning Jiang (2020)

Allow Misspellings of Length Function

Convenient aliases for common ways of misspelling the base R function length(). These include every permutation of the final three letters.

Automated Moderated Nonlinear Factor Analysis Using 'M-plus'

Automated generation, running, and interpretation of moderated nonlinear factor analysis models for obtaining scores from observed variables, using the method described by Gottfredson and colleagues (2019)