SOFTWARE

El GRID-BDS también desarrolla e implementa software libre (R: https://www.rproject.org) que permite a los investigadores y profesionales acceder a herramientas funcionales y fáciles de usar, para aplicar metodologías estadísticas en sus investigaciones.

Nombre: BwQuant
Autores: Conde-Amboage M, Sánchez-Sellero C.
Descripción: Bandwidth selectors for local linear quantile regression, including cross-validation and plug-in methods. The local linear quantile regression estimate is also implemented..
https://cran.r-project.org/web/packages/BwQuant/index.html

Nombre: neuroSCC
Autores: Arias Lopez A., Gomez Rubio V., Aguiar-Fernandez P., Haddon-Kemp A..
Descripción: Bridging Simultaneous Confidence Corridors and PET Neuroimaging: Tools for the structured processing of PET neuroimaging data in preparation for the estimation of Simultaneous Confidence Corridors (SCCs) for one-group, two-group, or single-patient vs group comparisons. The package facilitates PET image loading, data restructuring, integration into a Functional Data Analysis framework, contour extraction, identification of significant results, and performance evaluation. It bridges established packages (e.g., 'oro.nifti') with novel statistical methodologies (e.g., 'ImageSCC') and enables reproducible analysis pipelines, including comparison with Statistical Parametric Mapping ('SPM').
https://cran.r-project.org/web/packages/neuroSCC/index.html

Nombre: LearningStats
Autores: Borrajo-García MI, Conde-Amboage M.., López-Pérez A.
Descripción: Elemental Descriptive and Inferential Statistics: Provides tools to teach students elemental statistics. The main topics covered are descriptive statistics, probability models (discrete and continuous variables) and statistical inference (confidence intervals and hypothesis tests). One of the main advantages of this package is that allows the user to read quite a variety of types of data files with one unique command. Moreover it includes shortcuts to simple but up-to-now not in R descriptive features such a complete frequency table or an histogram with the optimal number of intervals. Related to model distributions (both discrete and continuous), the package allows the student to easy plot the mass/density function, distribution function and quantile function just detailing as input arguments the known population parameters. The inference related tools are basically confidence interval and hypothesis testing. Having defined independent commands for these two tools makes it easier for the student to understand what the software is performing, and it also helps the student to have a better knowledge on which specific tool they need to use in each situation. Moreover, the hypothesis testing commands provide not only the numeric result on the screen but also a very intuitive graph (which includes the statistic distribution, the observed value of the statistic, the rejection area and the p-value) that is very useful for the student to visualise the process. The regression section includes up to now, a simple linear model, with one single command the student can obtain the numeric summary as well as the corresponding diagram with the adjusted regression model and a legend with basic information (formula of the adjusted model and R-squared).
https://cran.r-project.org/web/packages/LearningStats/index.html

Nombre: smoothHR
Autores: Meira-Machado L., Araújo A., Cadarso-Suárez C., Gude F.
Descripción: an R package for pointwise nonparametric estimation of hazard ratio curves of continuous predictors.
http://cran.r-project.org/web/packages/smoothHR/smoothHR.pdf

Nombre: npROCRegression
Autores: Rodríguez-Álvarez, M.X., Roca-Pardiñas, J., Cadarso-Suárez, C.
Descripción: Incorporación de covariables dentro del análisis ROC desde una perspectiva no paramétrica.
https://CRAN.R-project.org/package=npROCRegression

Nombre: GsymPoint
Autores: López-Ratón, M., Cadarso-Suárez, C., Molanes, E., Letón, E..
Descripción: Estimación del punto de corte definido por el punto de simetría generalizada en un entorno de clasificación binaria basado en una prueba o marcador de diagnóstico continuo.
https://cran.r-project.org/web/packages/GsymPoint

Nombre: PREBED
Autores: Martínez-Silva, I., Rodríguez-Muiños, M.A., Diz-Dios P., Cadarso-Suárez, C.
Descripción: Software orientado a la aplicación odontológica, cuyo objetivo es la predicción del comportamiento de pacientes poco colaboradores (autistas, S. de Down y paralíticos cerebrales) ante una exploración oral y al someterse a tratamiento odontológico.

Nombre: tdc.msm
Autores: Meira-Machado, L., Cadarso-Suárez, C., de Uña-Álvarez, J..
Descripción: librería de R diseñada específicamente para el análisis de datos de supervivencia multi-estado. Permite definir un estado inicial (ej. diagnóstico), varios estados intermedios (ej. cambio de tratamiento, recaída o complicación) y un estado final o "absorbente" (ej. fallecimiento). Ofrece cinco tipos de modelos distintos para adaptarse a la naturaleza de los datos: Modelos de Cox Markov y Cox semi-Markov; Modelos de Markov homogéneos y no homogéneos; Modelos no paramétricos. Permite incluir variables que cambian con el tiempo (covariables dependientes del tiempo) para ver cómo afectan a la probabilidad de pasar de un estado a otro.
https://www.sciencedirect.com/science/article/abs/pii/S0169260707000156