Search results for "SAMPLE"
showing 10 items of 2270 documents
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…
Galaxy LIMS for next-generation sequencing.
2013
Abstract Summary: We have developed a laboratory information management system (LIMS) for a next-generation sequencing (NGS) laboratory within the existing Galaxy platform. The system provides lab technicians standard and customizable sample information forms, barcoded submission forms, tracking of input sample quality, multiplex-capable automatic flow cell design and automatically generated sample sheets to aid physical flow cell preparation. In addition, the platform provides the researcher with a user-friendly interface to create a request, submit accompanying samples, upload sample quality measurements and access to the sequencing results. As the LIMS is within the Galaxy platform, the …
Productivity, R&D Spillovers and Educational Attainment*
2012
Economists have long agreed that the local availability of a more qualified workforce generates significant spillovers. This study suggests that these externalities may arise because plants by having access to a more qualified workforce at a regional level, can benefit more from R&D spillovers than those located in areas with less qualified workforce. This hypothesis is tested on a sample of British establishments drawn from the Annual Business Inquiry over the period 1997–2002. The main results are consistent with our expectations that the regional differences in the industry-level educational attainment of the workforce available to a plant will condition its capability of absorbing R&D s…
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002
2007
Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …
Horvitz-Thompson estimators for functional data: asymptotic confidence bands and optimal allocation for stratified sampling
2009
When dealing with very large datasets of functional data, survey sampling approaches are useful in order to obtain estimators of simple functional quantities, without being obliged to store all the data. We propose here a Horvitz--Thompson estimator of the mean trajectory. In the context of a superpopulation framework, we prove under mild regularity conditions that we obtain uniformly consistent estimators of the mean function and of its variance function. With additional assumptions on the sampling design we state a functional Central Limit Theorem and deduce asymptotic confidence bands. Stratified sampling is studied in detail, and we also obtain a functional version of the usual optimal …
Latin hypercube sampling with inequality constraints
2010
International audience; In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algorithm to build a Latin hypercube sample (LHS) taking into account inequality constraints between the sampled variables. This technique, called constrained Latin hypercube sampling (cLHS), consists in doing permutations on an initial LHS to honor the desired monotonic constraints. The relevance of this approach is shown on a real example concerning the numerical w…
A computationally fast alternative to cross-validation in penalized Gaussian graphical models
2015
We study the problem of selection of regularization parameter in penalized Gaussian graphical models. When the goal is to obtain the model with good predicting power, cross validation is the gold standard. We present a new estimator of Kullback-Leibler loss in Gaussian Graphical model which provides a computationally fast alternative to cross-validation. The estimator is obtained by approximating leave-one-out-cross validation. Our approach is demonstrated on simulated data sets for various types of graphs. The proposed formula exhibits superior performance, especially in the typical small sample size scenario, compared to other available alternatives to cross validation, such as Akaike's i…
Sample-size calculation and reestimation for a semiparametric analysis of recurrent event data taking robust standard errors into account
2014
In some clinical trials, the repeated occurrence of the same type of event is of primary interest and the Andersen-Gill model has been proposed to analyze recurrent event data. Existing methods to determine the required sample size for an Andersen-Gill analysis rely on the strong assumption that all heterogeneity in the individuals' risk to experience events can be explained by known covariates. In practice, however, this assumption might be violated due to unknown or unmeasured covariates affecting the time to events. In these situations, the use of a robust variance estimate in calculating the test statistic is highly recommended to assure the type I error rate, but this will in turn decr…
Sample Size Requirements of a Mixture Analysis Method with Applications in Systematic Biology
1999
The available information on sample size requirements of mixture analysis methods is insufficient to permit a precise evaluation of the potential problems facing practical applications of mixture analysis. We use results from Monte Carlo simulation to assess the sample size requirements of a simple mixture analysis method under conditions relevant to biological applications of mixture analysis. The mixture model used includes two univariate normal components with equal variances but assumes that the researcher is ignorant as to the equality of the variances. The method used relies on the EM algorithm to compute the maximum likelihood estimates of the mixture parameters, and the likelihood r…
Central Limit Theorem for Linear Eigenvalue Statistics for a Tensor Product Version of Sample Covariance Matrices
2017
For $$k,m,n\in {\mathbb {N}}$$ , we consider $$n^k\times n^k$$ random matrices of the form $$\begin{aligned} {\mathcal {M}}_{n,m,k}({\mathbf {y}})=\sum _{\alpha =1}^m\tau _\alpha {Y_\alpha }Y_\alpha ^T,\quad {Y}_\alpha ={\mathbf {y}}_\alpha ^{(1)}\otimes \cdots \otimes {\mathbf {y}}_\alpha ^{(k)}, \end{aligned}$$ where $$\tau _{\alpha }$$ , $$\alpha \in [m]$$ , are real numbers and $${\mathbf {y}}_\alpha ^{(j)}$$ , $$\alpha \in [m]$$ , $$j\in [k]$$ , are i.i.d. copies of a normalized isotropic random vector $${\mathbf {y}}\in {\mathbb {R}}^n$$ . For every fixed $$k\ge 1$$ , if the Normalized Counting Measures of $$\{\tau _{\alpha }\}_{\alpha }$$ converge weakly as $$m,n\rightarrow \infty $$…