[PDF] Top 20 Factor Fiction A Monte Carlo Approach to Factor Analysis (ESRI Seminar Paper, 17 June 1975)

... It may be seen that the actual and estimated structures are quite similar, the highest correlation observed between estimates and actual being over 0: 9.It~ should, of course, be borne i[r] ... See full document

... critical factor that influences how new ideas become reduced to practice and recog- nized as a formal project through formation of a discov- ery project ... See full document

... When the volatility is randomly fluctuating, there is no analytic solution for GAO in general. To estimate unbiased prices of GAOs, we consider impor- tance sampling by applying the first order price approximations ... See full document

... Bayesian analysis in the radioactive waste characterization community, using a standard random walk Metropolis (RWM) Markov chain Monte Carlo (MCMC) algorithm [see 10, for details about ...Bayesian ... See full document

... HOESCHELE, 1996b A Monte Carlo method for Bayesian analysis of linkage between single markers and quantita- tive trait loci: 11. CORTESSIS, 1992 A Gibbs sampling approach[r] ... See full document

... Bayesian approach regarding the situation when we got high dimensional multivariate data relative to an even bigger number of ...regression approach where more accurate in terms to control bias and type I ... See full document

... our analysis includes also results in the technically demanding case of log-normal diffusion coefficients, where the differential operator depends in a non-affine way on the parameters, each of which is modelled ... See full document

... MC approach, the nuclear data are sampled at the beginning of the simulation, then the reactor core simulator that solves coupled multi-physics at different levels of approximation is ... See full document

... growth factor receptor family) signaling network with all four ErbB receptors and two ligands, epidermal growth factor (EGF) and heregulin ...simulation analysis led to new insights as to how the ... See full document

... this approach were suggested by a number of authors under different names ...error analysis, stopping rules, (iv) easily amenable to variance reduction techniques, (v) ideal for parallel ... See full document

... a Monte Carlo simulation. The Monte Carlo simulation is a well-known approach to model photon propagation within tissue [5, 6, 7, 8, ...a Monte Carlo model characterizes a ... See full document

... multiplication factor is considerably important in connection with the transient behavior of a reactor and this fact has associated nuclear criticality safety issues and must therefore be investigated since it has ... See full document

... Instead, we employ a Monte Carlo analysis. We generate random synthetic data sets with a single zone of uniform expansion and with the same noise as in our real data. We then compute the statistic ' ... See full document

... Integration (MCI) as proposed by Kloek and van Dijk (1978) and van Dijk and Kloek (1980) and further studied by Geweke (1986). This methodology is sufficiently general, allowing the computation of the posterior ... See full document

... probabilistic approach for cooperative multi-robot localization in indoor ...Our approach is based on Monte Carlo localization that has been applied with great practical success to single ... See full document

... the factor vector autoregressive model (F-VAR) framework is ...proposed approach shows mi- nimal pretesting requirements, performing well independently of integration properties of the data and sources of ... See full document

... of factor analysis is illustrated by means of an ...of factor reliability should accompany applied studies that utilize factor ...of factor reliability: use of split samples, ... See full document

... Monte Carlo simulation performs risk analysis by building models of possible results by substituting a range of values—a probability distribution—for any factor that has inherent ...a ... See full document

... probabilistic analysis to evaluate landslide-triggering thresholds in the presence of ...the analysis of correct and wrong predictions, may be advantageously applied as well ... See full document

... quasi-Monte Carlo sequences). As well known, quasi-Monte Carlo methods have better convergence rate, at least asymptotically, of O(log d N/N ), whereas Monte Carlo methods have ... See full document