Using R via PHP for Teaching Purposes: R-php

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 computer mouse. We think that this tool could be particularly useful for teaching purposes: one possible use could be in a University computer laboratory to permit a smooth approach of students to R.

A Software Tool for the Exponential Power Distribution: The normalp Package

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo-random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studies to see the suitability of the estimators used. Some examples of use of this package are provided.

Using R via PHP for Teaching Purposes: R-php

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 computer mouse. We think that this tool could be particularly useful for teaching purposes: one possible use could be in a University computer laboratory to permit a smooth approach of students to R

Using R via PHP for Teaching Purposes: R-php

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 computer mouse. We think that this tool could be particularly useful for teaching purposes: one possible use could be in a University computer laboratory to permit a smooth approach of students to R

Generalized information criterion for model selection in penalized graphical models

This paper introduces an estimator of the relative directed distance between an estimated model and the true model, based on the Kulback-Leibler divergence and is motivated by the generalized information criterion proposed by Konishi and Kitagawa. This estimator can be used to select model in penalized Gaussian copula graphical models. The use of this estimator is not feasible for high-dimensional cases. However, we derive an efficient way to compute this estimator which is feasible for the latter class of problems. Moreover, this estimator is, generally, appropriate for several penalties such as lasso, adaptive lasso and smoothly clipped absolute deviation penalty. Simulations show that the method performs similarly to KL oracle estimator and it also improves BIC performance in terms of support recovery of the graph. Specifically, we compare our method with Akaike information criterion, Bayesian information criterion and cross validation for band, sparse and dense network structures

A Software Tool for the Exponential Power Distribution: The normalp Package

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo\u2013random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studies to see the suitability of the estimators used. Some examples of use of this package are provided

Using differential geometric lars algorithm to study the expression profile of a sample of patients with latex-fruit syndrome

Natural rubber latex IgE-mediated hypersensitivity is one of the most important health problems in allergy during recent years. The prevalence of individuals allergic to latex shows an associated hypersensitivity to some plant-derived foods, especially freshly consumed fruit. This association of latex allergy and allergy to plant-derived foods is called latex-fruit syndrome. The aim of this study is to use the differential geometric generalization of the LARS algorithm to identify candidate genes that may be associated with the pathogenesis of allergy to latex or vegetable

SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS

The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data

Augmented Reality to Guide Selective Clamping and Tumor Dissection During Robot-assisted Partial Nephrectomy: A Preliminary Experience.

ABSTRACT Introduction to explore the feasibility of augmented reality (AR) to guide arterial clamping during robot-assisted partial nephrectomy (RAPN). Patients and Methods 15 consecutive patients with T1 renal mass underwent RAPN guided by AR. The 3D virtual model derived by computed tomography was superimposed on the actual view provided by the Da Vinci video stream thought AR technology. Preoperative plan of arterial clamping based on 2D conventional imaging, on 3D model and the effective intraoperative surgical approach guided by AR were compared using the McNeamar test. Results The plan of arterial clamping based on 2D preoperative imaging was recorded as follows: no clamping in 3 (20%), clamping of the main artery in 10 (66.7%) and selective clamping in 1 (6.7%) and super-selective clamping in 1 (6.7%) cases. After revision of the 3D model, the plan of clamping was modified as follows: no clamping in 1 (6.7%), clamping of the main artery in 2 (13.3%), selective clamping in 8 (53.3%) and super-selective clamping in 4 (26.7%) cases (p=0.03). The effective intraoperative clamping approach guided by AR-guidance was performed as planned in 13 (86.7%) patients. Conclusion AR for 3D guided renal surgery is useful to increase the adoption of selective clamping during RAPN