Search results for "certainty"
showing 10 items of 1057 documents
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…
Nonequilibrium electron spin relaxation in n-type doped GaAs sample
2019
Non-equilibrium electron spin relaxation in a n-type doped GaAs bulk semiconductor is investigated. We use a semiclassical Monte Carlo approach by considering multivalley spin dynamics of drifting electrons. Spin relaxation is considered through the D'yakonov-Perel mechanism, which is the dominant process in III-V semiconductors. An analytical expression for the inhomogeneous broadening of spin precession vector is derived by taking into account the effect of the electric field and the doping density. The inclusion of electron-electron scattering has the effect of increasing both the spin lifetime and the depolarization length. In particular, we find a non-monotonic trend with the maximum o…
WOODIV, a database of occurrences, functional traits, and phylogenetic data for all Euro-Mediterranean trees
2021
Trees play a key role in the structure and function of many ecosystems worldwide. In the Mediterranean Basin, forests cover approximately 22% of the total land area hosting a large number of endemics (46 species). Despite its particularities and vulnerability, the biodiversity of Mediterranean trees is not well known at the taxonomic, spatial, functional, and genetic levels required for conservation applications. The WOODIV database fills this gap by providing reliable occurrences, four functional traits (plant height, seed mass, wood density, and specific leaf area), and sequences from three DNA-regions (rbcL, matK, and trnH-psbA), together with modelled occurrences and a phylogeny for all…
Spanish electoral archive. SEA database
2021
This paper introduces the SEA database (acronym for Spanish Electoral Archive). SEA brings together the most complete public repository available to date on Spanish election outcomes. SEA holds all the results recorded from the electoral processes of General (1979–2019), Regional (1989–2021), Local (1979–2019) and European Parliamentary (1987–2019) elections held in Spain since the restoration of democracy in the late 70 s, in addition to other data sets with electoral content. The data are offered for free and is presented in a homogeneous and friendly format. Most of the databases are available for download with data from various electoral levels, including from the ballot box level. This…
A database for the monitoring of thermal anomalies over the Amazon forest and adjacent intertropical oceans
2015
AbstractAdvances in information technologies and accessibility to climate and satellite data in recent years have favored the development of web-based tools with user-friendly interfaces in order to facilitate the dissemination of geo/biophysical products. These products are useful for the analysis of the impact of global warming over different biomes. In particular, the study of the Amazon forest responses to drought have recently received attention by the scientific community due to the occurrence of two extreme droughts and sustained warming over the last decade. Thermal Amazoni@ is a web-based platform for the visualization and download of surface thermal anomalies products over the Ama…
Statistical inference and Monte Carlo algorithms
1996
This review article looks at a small part of the picture of the interrelationship between statistical theory and computational algorithms, especially the Gibbs sampler and the Accept-Reject algorithm. We pay particular attention to how the methodologies affect and complement each other.
Ergodicity for a stochastic Hodgkin–Huxley model driven by Ornstein–Uhlenbeck type input
2013
We consider a model describing a neuron and the input it receives from its dendritic tree when this input is a random perturbation of a periodic deterministic signal, driven by an Ornstein-Uhlenbeck process. The neuron itself is modeled by a variant of the classical Hodgkin-Huxley model. Using the existence of an accessible point where the weak Hoermander condition holds and the fact that the coefficients of the system are analytic, we show that the system is non-degenerate. The existence of a Lyapunov function allows to deduce the existence of (at most a finite number of) extremal invariant measures for the process. As a consequence, the complexity of the system is drastically reduced in c…
Variance Estimation and Asymptotic Confidence Bands for the Mean Estimator of Sampled Functional Data with High Entropy Unequal Probability Sampling …
2013
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the Hajek formula. The interest of this asymptotic variance approximation is that it only involves the first order inclusion probabilities of the statistical units. We extend this variance formula when the variable under study is functional and we prove, under general conditions on the regularity of the individual trajectories and the sampling design, that it asymptotically provides a uniformly consistent estimator of the variance function of the Horvitz-Thompson estimator of the mean function. Rates of convergence to the true variance function are gi…
Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity
2014
Recent development of intensity estimation for inhomogeneous spatial point processes with covariates suggests that kerneling in the covariate space is a competitive intensity estimation method for inhomogeneous Poisson processes. It is not known whether this advantageous performance is still valid when the points interact. In the simplest common case, this happens, for example, when the objects presented as points have a spatial dimension. In this paper, kerneling in the covariate space is extended to Gibbs processes with covariates-dependent chemical activity and inhibitive interactions, and the performance of the approach is studied through extensive simulation experiments. It is demonstr…
Graphical representation of some duality relations in stochastic population models
2007
We derive a unified stochastic picture for the duality of a resampling-selection model with a branching-coalescing particle process (cf. http://www.ams.org/mathscinet-getitem?mr=MR2123250) and for the self-duality of Feller's branching diffusion with logistic growth (cf. math/0509612). The two dual processes are approximated by particle processes which are forward and backward processes in a graphical representation. We identify duality relations between the basic building blocks of the particle processes which lead to the two dualities mentioned above.