Estimate Procedure in Case of First Order Autocorrelation

Solve first order autocorrelation problems using an iterative method. This procedure estimates both autocorrelation and beta coefficients recursively until we reach the convergence (8th decimal as default). The residuals are computed after estimating Beta using EGLS approach and Rho is estimated using the previous residuals.

R Commander

A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.

Knowledge Discovery by Accuracy Maximization

A self-guided, weakly supervised learning algorithm for feature extraction from noisy and high-dimensional data. It facilitates the identification of patterns that reflect underlying group structures across all samples in a dataset. The method incorporates a novel strategy to integrate spatial information, improving the interpretability of results in spatially resolved data.

Implement Fleming-Viot-Dependent Dirichlet Processes

A Bayesian Nonparametric model for the study of time-evolving frequencies, which has become renowned in the study of population genetics. The model consists of a Hidden Markov Model (HMM) in which the latent signal is a distribution-valued stochastic process that takes the form of a finite mixture of Dirichlet Processes, indexed by vectors that count how many times each value is observed in the population. The package implements methodologies presented in Ascolani, Lijoi and Ruggiero (2021) and Ascolani, Lijoi and Ruggiero (2023) that make it possible to study the process at the time of data collection or to predict its evolution in future or in the past.

Spatial KWD for Large Spatial Maps

Contains efficient implementations of Discrete Optimal Transport algorithms for the computation of Kantorovich-Wasserstein distances between pairs of large spatial maps (Bassetti, Gualandi, Veneroni (2020), ). All the algorithms are based on an ad-hoc implementation of the Network Simplex algorithm. The package has four main helper functions: compareOneToOne() (to compare two spatial maps), compareOneToMany() (to compare a reference map with a list of other maps), compareAll() (to compute a matrix of distances between a list of maps), and focusArea() (to compute the KWD distance within a focus area). In non-convex maps, the helper functions first build the convex-hull of the input bins and pad the weights with zeros.

A Service for Tidy Transcriptomics Software Suite

It provides generic methods that are used by more than one package, avoiding conflicts. This package will be imported by 'tidySingleCellExperiment' and 'tidyseurat'.

Tidy Prediction and Plotting of Generalised Additive Models

Provides functions that compute predictions from Generalised Additive Models (GAMs) fitted with 'mgcv' and return them as a tibble. These can be plotted with a generic plot()-method that uses 'ggplot2' or plotted as any other data frame. The main function is predict_gam().

Articulatory Data Processing in R

A tool for processing Articulate Assistant Advanced™ (AAA) ultrasound tongue imaging data and Carstens AG500/1 electro-magnetic articulographic data.

Extra Functionality for 'leaflet' Package

The 'leaflet' JavaScript library provides many plugins some of which are available in the core 'leaflet' package, but there are many more. It is not possible to support them all in the core 'leaflet' package. This package serves as an add-on to the 'leaflet' package by providing extra functionality via 'leaflet' plugins.

Brings Seurat to the Tidyverse

It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.