Search results for "Programming language"
showing 10 items of 624 documents
Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp
2017
Blind source separation (BSS) is a well-known signal processing tool which is used to solve practical data analysis problems in various fields of science. In BSS, we assume that the observed data consists of linear mixtures of latent variables. The mixing system and the distributions of the latent variables are unknown. The aim is to find an estimate of an unmixing matrix which then transforms the observed data back to latent sources. In this paper we present the R packages JADE and BSSasymp. The package JADE offers several BSS methods which are based on joint diagonalization. Package BSSasymp contains functions for computing the asymptotic covariance matrices as well as their data-based es…
Spatio-temporal modelling of COVID-19 incident cases using Richards’ curve: An application to the Italian regions
2021
Abstract We introduce an extended generalised logistic growth model for discrete outcomes, in which spatial and temporal dependence are dealt with the specification of a network structure within an Auto-Regressive approach. A major challenge concerns the specification of the network structure, crucial to consistently estimate the canonical parameters of the generalised logistic curve, e.g. peak time and height. We compared a network based on geographic proximity and one built on historical data of transport exchanges between regions. Parameters are estimated under the Bayesian framework, using Stan probabilistic programming language. The proposed approach is motivated by the analysis of bot…
Introducing libeemd: a program package for performing the ensemble empirical mode decomposition
2016
The ensemble empirical mode decomposition (EEMD) and its complete variant (CEEMDAN) are adaptive, noise-assisted data analysis methods that improve on the ordinary empirical mode decomposition (EMD). All these methods decompose possibly nonlinear and/or nonstationary time series data into a finite amount of components separated by instantaneous frequencies. This decomposition provides a powerful method to look into the different processes behind a given time series data, and provides a way to separate short time-scale events from a general trend. We present a free software implementation of EMD, EEMD and CEEMDAN and give an overview of the EMD methodology and the algorithms used in the deco…
Bayesian survival analysis with BUGS
2020
Survival analysis is one of the most important fields of statistics in medicine and biological sciences. In addition, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this article is to summarize some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programmin…
Identifying Causal Effects with the R Package causaleffect
2017
Do-calculus is concerned with estimating the interventional distribution of an action from the observed joint probability distribution of the variables in a given causal structure. All identifiable causal effects can be derived using the rules of do-calculus, but the rules themselves do not give any direct indication whether the effect in question is identifiable or not. Shpitser and Pearl constructed an algorithm for identifying joint interventional distributions in causal models, which contain unobserved variables and induce directed acyclic graphs. This algorithm can be seen as a repeated application of the rules of do-calculus and known properties of probabilities, and it ultimately eit…
Using R via PHP for Teaching Purposes: R-php
2006
This paper deals with the R-php statistical software, that is an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on R. Indeed, this software uses, as "engine" for statistical analyses, R via PHP and its design has been inspired by a paper of de Leeuw (1997). R-php is based on two modules: a base module and a point-and-click module. R-php base allows the simple editing of R code in a form. R-php point-and-click allows some statistical analyses by means of a graphical user interface (GUI): then, to use this module it is not necessary for the user to know the R environment, but all the allowed analyses can be performed by using the compu…
On surrogating 0–1 knapsack constraints
1999
In this note, we present a scheme for tightening 0–1 knapsack constraints based on other knapsack constraints surrogating.
Multiple sequence editing by spreadsheet.
1990
Spreadsheets have several functions and facilities that make them good candidates to be used as multiple sequence editors. They can be easily programmed (even by non-programmers) with macros that allow them to fit the needs of the user, free of the restrictions that programs written by other people have. Here I present a sheet containing a set of macros written for Lotus 1-2-3
NeoFox: annotating neoantigen candidates with neoantigen features
2020
Abstract Summary The detection and prediction of true neoantigens is of great importance for the field of cancer immunotherapy. Wesearched the literature for proposed neoantigen features and integrated them into a toolbox called NEOantigen Feature toolbOX (NeoFox). NeoFox is an easy-to-use Python package that enables the annotation of neoantigen candidates with 16 neoantigen features. Availability and implementation NeoFox is freely available as an open source Python package released under the GNU General Public License (GPL) v3 license at https://github.com/TRON-Bioinformatics/neofox. Supplementary information Supplementary data are available at Bioinformatics online.
Flexible latent trait aggregation to analyze employability after the Ph.D. in Italy
2015
The analysis of satisfaction, employability and economic perspectives after the Ph.D. in Italy has not received adequate attention in the past, especially in terms of comparison among universities. To analyze these aspects, in this paper we consider data from the survey ‘Statistica in TEma di Laureati e LAvoro’ on doctors who achieved the title on 2007, 2008 and 2009 [CILEA, Laureati STELLA, indagine occupazionale post-dottorato, dottori di ricerca 2007–2008, Tech. Rep., CILEA, Segrate, 2010; CILEA,Laureati STELLA, indagine occupazionale post-dottorato, dottori di ricerca 2008–2009, Tech. Rep., CILEA, Segrate, 2011]. To deal with the complex, multidimensional nature of the concept, we propo…