Search results for "Uncertainty"
showing 10 items of 1010 documents
An extended continuous mapping theorem for outer almost sure weak convergence
2019
International audience; We prove an extended continuous mapping theorem for outer almost sure weak convergence in a metric space, a notion that is used in bootstrap empirical processes theory. Then we make use of those results to establish the consistency of several bootstrap procedures in empirical likelihood theory for functional parameters.
IndElec: A Software for Analyzing Party Systems and Electoral Systems
2011
IndElec is a software addressed to compute a wide range of indices from electoral data, which are intended to analyze both party systems and electoral systems in political studies. Further, IndElec can calculate such indices from electoral data at several levels of aggregation, even when the acronyms of some political parties change across districts. As the amount of information provided by IndElec may be considerable, this software also aids the user in the analysis of electoral data through three capabilities. First, IndElec automatically elaborates preliminary descriptive statistical reports of computed indices. Second, IndElec saves the computed information into text files in data matri…
Meta-work and the analogous Jarzynski relation in ensembles of dynamical trajectories
2014
Recently there has been growing interest in extending the thermodynamic method from static configurations to dynamical trajectories. In this approach, ensembles of trajectories are treated in an analogous manner to ensembles of configurations in equilibrium statistical mechanics: generating functions of dynamical observables are interpreted as partition sums, and the statistical properties of trajectory ensembles are encoded in free-energy functions that can be obtained through large-deviation methods in a suitable large time limit. This establishes what one can call a 'thermodynamics of trajectories'. In this paper we go a step further, and make a first connection to fluctuation theorems b…
Graphical User Interfaces for R
2012
Since R was first launched, it has managed to gain the support of an ever-increasing percentage of academic and professional statisticians. However, the spread of its use among novice and occasional users of statistics have not progressed at the same pace, which can be attributed partially to the lack of a graphical user interface (GUI). Nevertheless, this situation has changed in the last years and there is currently several projects that have added GUIs to R. This article discusses briefly the history of GUIs for data analysis and then introduces the papers submitted to an special issue of the Journal of Statistical Software on GUIs for R.
On delocalization of eigenvectors of random non-Hermitian matrices
2019
We study delocalization of null vectors and eigenvectors of random matrices with i.i.d entries. Let $A$ be an $n\times n$ random matrix with i.i.d real subgaussian entries of zero mean and unit variance. We show that with probability at least $1-e^{-\log^{2} n}$ $$ \min\limits_{I\subset[n],\,|I|= m}\|{\bf v}_I\| \geq \frac{m^{3/2}}{n^{3/2}\log^Cn}\|{\bf v}\| $$ for any real eigenvector ${\bf v}$ and any $m\in[\log^C n,n]$, where ${\bf v}_I$ denotes the restriction of ${\bf v}$ to $I$. Further, when the entries of $A$ are complex, with i.i.d real and imaginary parts, we show that with probability at least $1-e^{-\log^{2} n}$ all eigenvectors of $A$ are delocalized in the sense that $$ \min\l…
A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS
2019
We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…
Large-distance asymptotic behaviour of multi-point correlation functions in massless quantum models
2014
We provide a microscopic model setting that allows us to readily access to the large-distance asymptotic behaviour of multi-point correlation functions in massless, one-dimensional, quantum models. The method of analysis we propose is based on the form factor expansion of the correlation functions and does not build on any field theory reasonings. It constitutes an extension of the restricted sum techniques leading to the large-distance asymptotic behaviour of two-point correlation functions obtained previously.
Bayesian measures of surprise for outlier detection
2003
From a Bayesian point of view, testing whether an observation is an outlier is usually reduced to a testing problem concerning a parameter of a contaminating distribution. This requires elicitation of both (i) the contaminating distribution that generates the outlier and (ii) prior distributions on its parameters. However, very little information is typically available about how the possible outlier could have been generated. Thus easy, preliminary checks in which these assessments can often be avoided may prove useful. Several such measures of surprise are derived for outlier detection in normal models. Results are applied to several examples. Default Bayes factors, where the contaminating…
Electricity consumption prediction with functional linear regression using spline estimators
2010
A functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. This model serves to analyse a real data set describing electricity consumption in Sardinia. The interest lies in predicting either oncoming weekends’ or oncoming weekdays’ consumption, provided actual weekdays’ consumption is known. A B-spline estimator of the functional parameter is used. Selected computational issues are addressed as well.
What subject matter questions motivate the use of machine learning approaches compared to statistical models for probability prediction?
2014
This is a discussion of the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler.