Search results for "47"
showing 10 items of 1382 documents
Anthropometry: An R Package for Analysis of Anthropometric Data
2017
The development of powerful new 3D scanning techniques has enabled the generation of large up-to-date anthropometric databases which provide highly valued data to improve the ergonomic design of products adapted to the user population. As a consequence, Ergonomics and Anthropometry are two increasingly quantitative fields, so advanced statistical methodologies and modern software tools are required to get the maximum benefit from anthropometric data. This paper presents a new R package, called Anthropometry, which is available on the Comprehensive R Archive Network. It brings together some statistical methodologies concerning clustering, statistical shape analysis, statistical archetypal an…
Recurrence Plots in Nonlinear Time Series Analysis: Free Software
2002
Recurrence plots are graphical devices specially suited to detect hidden dynamical patterns and nonlinearities in data. However, there are few programs available to apply such a mehodology. This paper reviews one of the best free programs to apply nonlinear time series analysis: Visual Recurrence Analysis (VRA). This program is targeted to recurrence analysis and the so-called Recurrence Quantitative Analysis (RQA, the quantitative counterpart of recurrence plots), although it includes many procedures in a friendly visual environment. Comparisons with alternative programs are performed.
Testing Goodness-of-Fit with the Kernel Density Estimator: GoFKernel
2015
To assess the goodness-of-fit of a sample to a continuous random distribution, the most popular approach has been based on measuring, using either L∞ - or L2 -norms, the distance between the null hypothesis cumulative distribution function and the empirical cumulative distribution function. Indeed, as far as I know, almost all the tests currently available in R related to this issue (ks.test in package stats, ad.test in package ADGofTest, and ad.test, ad2.test, ks.test, v.test and w2.test in package truncgof) use one of these two distances on cumulative distribution functions. This paper (i) proposes dgeometric.test, a new implementation of the test that measures the discrepancy between a s…
Dynamic-Interactive Graphics for Statistics (26 years later)
2014
This paper briefly reviews the history of dynamic-interactive graphicsfor statistics, introduces an example of such graphics, and provides a fewglimpses as to the current state of things and the future trends we envision.The general conclusion is that dynamic-interactive graphics for statistics arethriving more than ever as they shift from the desktop to the internet. Thus,dynamic-interactive graphics are becoming increasingly important as they: 1) provide non-experts in statistics with the means to carry out analyses on their own; and 2) teach the basic concepts of statistics to students and practitioners with low to moderate mathematics skills. Their increasingpopularity makes the lesson…
Analyzing Temperature Effects on Mortality Within theREnvironment: The Constrained Segmented Distributed Lag Parameterization
2010
Here we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.
Mixed Non-Parametric and Parametric Estimation Techniques in R Package etasFLP for Earthquakes’ Description
2017
etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquake catalog; non-parametric background seismicity can be estimated through a forward predictive likelihood approach, while parametric components of triggered seismicity are estimated through maximum likelihood; estimation steps are alternated until convergence is obtained and for each event the probability of being a background event is estimated. The package includes options which allow its wide use. Methods for plot, summary and profile are defined for the main output class object. The paper provides examples of the package's use with description of the underlying R and Fortran routines.
R Graphics (3rd Edition)
2020
A Software Tool for the Exponential Power Distribution: The normalp Package
2005
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 studi…
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…