Estimación de conjuntos en esferas
We provide an R tool for nonparametric plug-in estimation of Highest Density Regions (HDRs) in the directional setting. Concretely, circular and spherical regions can be reconstructed from a data sample following Saavedra-Nieves and Crujeiras (2020) <arXiv:2009.08915>. This library also contains two real datasets in the circular and spherical settings. The first one concerns a problem from animal orientation studies and the second one is related to earthquakes occurrences.
Aquí se incluyen un conjunto de funciones que permiten realizar cálculos matemáticos (calculadora, derivación, integración, ecuaciones diferenciales, sistemas de ecuaciones diferenciales por métodos analíticos y numéricos etc.), estadísticos (test de hipotesis, test de normalidad, intervalos de confianza y de tolerancia, calculos de k(P/p), etc), ajustes de curvas, representaciones gráficas en 2D y 3D, optimización lineal y no lineal y más cosas. Si necesitas realizar cálculos que no se puedan realizar con las herramientas habituales puedes proponer que se incluyan aquí. Observa que una de las grandes ventajas es que estos estarán disponibles desde cualquier ordenador que esté conectado a Internet.
Detección de modas
Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2019 <doi:10.1007/s11749-018-0611-5>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques <doi:10.18637/jss.v097.i09>.
Inferencia sobre datos circulares
Incorporación de covariables dentro del análisis ROC desde una perspectiva no paramétrica.
Computing optimal cutpoints in diagnostic tests.
Multivariate analysis with application to biomedicine
ORdensity gives the user the list of genes identified as differentially expressed genes in an easy and comprehensible way. The experimentation carried out in an off-the-self computer with the parallel execution enabled shows an improvement in run-time. This implementation may also lead to an important use of memory load. Results previously obtained with simulated and real data indicated that the procedure implemented in the package is robust and suitable for differentially expressed genes identification.
p3state.msm provides functions for estimating semi-parametric regression models but also to implement nonparametric estimators for the transition probabilities. The methods can also be used in progressive three-state models. In progressive three-state models, estimators for other quantities such as the bivariate distribution function (for the sequentially ordered events) are also given.
Multiple testing
This package implements seven different methods for multiple testing problems. The Benjamini and Hochberg (1995) false discovery rate controlling procedure and its modification for dependent tests Benjamini and Yekutieli (2001), the method called Binomial SGoF proposed in Carvajal Rodríguez et al. (2009) and its conservative and bayesian versions called Conservative SGoF (de Uña Álvarez, 2011) and Bayesian SGoF (Castro Conde and de Uña Álvarez, 2013 13/06), respectively, and the BB-SGoF (Beta-Binomial SGoF, de Uña Álvarez, 2012) and Discrete SGoF (Castro Conde et al., 2015) procedures which are adaptations of SGoF method for possibly correlated tests and for discrete tests, respectively. Number of rejections, FDR and adjusted p-values are computed among other things.
Teaching
This is a collection of programs to illustrate themes in teaching statistics, such as the central limit theorem, confidence intervals, bootstrapping, nonparametric statistics
Librería para el package estadístico R, llamado TPmsm, para la obtención de estimaciones paramétricas y semiparamétricas de las probabilidades de transición en modelos de multiestado com tres estados.