Several functions introduced in Aster et al.'s book on inverse theory. The functions are often translations of MATLAB code developed by the authors to illustrate concepts of inverse theory as applied to geophysics. Generalized inversion, tomographic inversion algorithms (conjugate gradients, ART and SIRT'), non-linear least squares, first and second order Tikhonov regularization, roughness constraints, and procedures for estimating smoothing parameters are included.

Drawing population pyramid using (1) data.frame or (2) vectors. The former is named as pyramid() and the latter pyramids(), as wrapper function of pyramid(). pyramidf() is the function to draw population pyramid within the specified frame.

Fits single- and multiple-group penalized factor analysis models via a trust-region algorithm with integrated automatic multiple tuning parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>). Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.

Obtener listado de datos, acceder y extender series del Portal de Datos de Hacienda.Las proyecciones se realizan con forecast', Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>. Search, download and forecast time-series from the Ministry of Economy of Argentina. Forecasts are built with the forecast package, Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>.

There are two main functions: (1) To estimate the power of testing for linkage using an affected sib pair design, as a function of the recurrence risk ratios. We will use analytical power formulae as implemented in R. These are based on a Mathematica notebook created by Martin Farrall. (2) To examine how the power of the transmission disequilibrium test (TDT) depends on the disease allele frequency, the marker allele frequency, the strength of the linkage disequilibrium, and the magnitude of the genetic effect. We will use an R program that implements the power formulae of Abel and Muller-Myhsok (1998). These formulae allow one to quickly compute power of the TDT approach under a variety of different conditions. This R program was modeled on Martin Farrall's Mathematica notebook.

Provide estimation for particular cases of the power series cure rate model <doi:10.1080/03610918.2011.639971>. For the distribution of the concurrent causes the alternative models are the Poisson, logarithmic, negative binomial and Bernoulli (which are includes in the original work), the polylogarithm model <doi:10.1080/00949655.2018.1451850> and the Flory-Schulz <doi:10.3390/math10244643>. The estimation procedure is based on the EM algorithm discussed in <doi:10.1080/03610918.2016.1202276>. For the distribution of the time-to-event the alternative models are slash half-normal, Weibull, gamma and Birnbaum-Saunders distributions.

Simulate and run the Gaussian puff forward atmospheric model in sensor (specific sensor coordinates) or grid (across the grid of a full oil and gas operations site) modes, following Jia, M., Fish, R., Daniels, W., Sprinkle, B. and Hammerling, D. (2024) <doi:10.26434/chemrxiv-2023-hc95q-v3>. Numerous visualization options, including static and animated, 2D and 3D, and a site map generator based on sensor and source coordinates.

Particle swarm optimization - a basic variant.

Generic code for estimating treatment effects with panel data. The idea is to break into separate steps organizing the data, looping over groups and time periods, computing group-time average treatment effects, and aggregating group-time average treatment effects. Often, one is able to implement a new identification/estimation procedure by simply replacing the step on estimating group-time average treatment effects. See several different examples of this approach in the package documentation.

In the era of big data, data redundancy and distributed characteristics present novel challenges to data analysis. This package introduces a method for estimating optimal subsets of redundant distributed data, based on PPCDT (Conjunction of Power and P-value in Distributed Settings). Leveraging PPC technology, this approach can efficiently extract valuable information from redundant distributed data and determine the optimal subset. Experimental results demonstrate that this method not only enhances data quality and utilization efficiency but also assesses its performance effectively. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.

This package contains functions to classify the pixels of an image file by its colour. It implements a simple form of the techniques known as Support Vector Machine adapted to this particular problem.

Fast tools for fitting sparse generalized linear models with convex penalties (lasso) and concave penalties (smoothly clipped absolute deviation and minimax concave penalty). Computation uses multi-stage convex relaxation and pathwise coordinate optimization with warm starts, active-set updates, and screening rules. Core solvers are implemented in C++, and coefficient paths are stored as sparse matrices for memory efficiency.

Set of tools for reading, writing and transforming spatial and seasonal data, model selection and specific statistical tests for ecologists. It includes functions to interpolate regular positions of points between landmarks, to discretize polylines into regular point positions, link distant observations to points and convert a bounding box in a spatial object. It also provides miscellaneous functions for field ecologists such as spatial statistics and inference on diversity indexes, writing data.frame with Chinese characters.

Chromatin immunoprecipitation DNA sequencing results in genomic tracks that show enriched regions or peaks where proteins are bound. This package implements fast C code that computes the true and false positives with respect to a database of annotated region labels.

Receiver Operating Characteristic (ROC) analysis is performed assuming samples are from the Power Lindley distribution. Specificity, sensitivity, area under the curve and ROC curve are provided.

Proteins reside in either the cell plasma or in the cell membrane. A membrane protein goes through the membrane at least once. Given the amino acid sequence of a membrane protein, the tool PureseqTM (<https://github.com/PureseqTM/pureseqTM_package>, as described in "Efficient And Accurate Prediction Of Transmembrane Topology From Amino acid sequence only.", Wang, Qing, et al (2019), <doi:10.1101/627307>), can predict the topology of a membrane protein. This package allows one to use PureseqTM from R.

An enterprise-targeted scalable and UI-standardized shiny framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.

Producing the time-dependent receiver operating characteristic (ROC) curve through parametric approaches. Tools for generating random data, fitting, predicting and check goodness of fit are prepared. The methods are developed from the theoretical framework of proportional hazard model and copula functions. Using this package, users can now simulate parametric time-dependent ROC and run experiment to understand the behavior of the curve under different scenario.

This package performs partial principal component analysis of a large sparse matrix. The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally. Useful application includes cases where the number of total nonzero entries exceed the capacity of 32 bit integers (e.g., with large Single Nucleotide Polymorphism data).

This package provides a comprehensive package for detecting and analyzing causal relationships in complex systems using pattern-based approaches. Key features include state space reconstruction, pattern identification, and causality strength evaluation.

The goal of PlotFTIR is to easily and quickly kick-start the production of journal-quality Fourier Transform Infra-Red (FTIR) spectral plots in R using ggplot2'. The produced plots can be published directly or further modified by ggplot2 functions. L'objectif de PlotFTIR est de démarrer facilement et rapidement la production des tracés spectraux de spectroscopie infrarouge à transformée de Fourier (IRTF) de qualité journal dans R à l'aide de ggplot2'. Les tracés produits peuvent être publiés directement ou modifiés davantage par les fonctions ggplot2'.

Pedigree related functions.

Fitting and testing probabilistic knowledge structures, especially the basic local independence model (BLIM, Doignon & Flamagne, 1999) and the simple learning model (SLM), using the minimum discrepancy maximum likelihood (MDML) method (Heller & Wickelmaier, 2013 <doi:10.1016/j.endm.2013.05.145>).

Fast and Accurate Randomized Singular Value Decomposition (RSVD) methods proposed in the PCAone paper by Li (2023) <https://genome.cshlp.org/content/33/9/1599>.