搜索结果: 1-15 共查到“统计学 Statistical Inference”相关记录18条 . 查询时间(0.062 秒)
Approximation of epidemic models by diffusion processes and their statistical inference
Approximation epidemic models diffusion processes their statistical inference
2013/6/14
Among various mathematical frameworks, multidimensional continuous-time Markov jump processes $(Z_t)$ on $\N^d$ form a natural set-up for modeling $SIR$-like epidemics. In this study we extend the res...
An ANOVA Test for Parameter Estimability using Data Cloning with Application to Statistical Inference for Dynamic Systems
Maximum Likelihood Estimation Over -Parametrized Models Markov Chain Monte Carlo Parameter Identifiability Differential Equation Models
2013/6/14
Models for complex systems are often built with more parameters than can be uniquely identified by available data. Because of the variety of causes, identifying a lack of parameter identifiability typ...
Statistical Inference For Persistent Homology
persistent homology topology density estimation
2013/4/28
Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features as one varies a tuning parame...
Statistical inference for Sobol pick freeze Monte Carlo method
Statistical inference Sobol pick freeze Monte Carlo method
2013/4/28
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Statistical inference for discrete-time samples from affine stochastic delay differential equations
asymptotic normality composite likelihood consistency discrete time observation of continuous-time models prediction-based estimating functions pseudo-likelihood stochastic delay differential equation
2013/4/28
Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to cal...
Statistical inference in compound functional models
Compound functional model minimax estimation sparse additive structure dimen-sion reduction structure adaptation
2012/9/18
We consider a general nonparametric regression model called the compound model. It includes,as special cases, sparse additive regression and nonparametric (or linear) regression with many covariates b...
Statistical Inference of Allopolyploid Species Networks in the Presence of Incomplete Lineage Sorting
Allopolyploid hybridization Bayesian phylogenetics network
2012/9/18
Polyploidy is an important speciation mechanism, particularly in land plants. Allopolyploid species are formed after hybridization betweenother-wise intersterile parental species. Recent theoretical p...
Discussion of "Statistical Inference: The Big Picture" by R. E. Kass
Discussion Statistical Inference The Big Picture R. E. Kass
2011/7/6
Rob Kass presents a fascinating vision of a “post”-Bayes/frequentist-controversy world in which prac-tical utility of statistical models is the guiding prin-ciple for statistical inference.
Discussion of "Statistical Inference: The Big Picture" by R. E. Kass
Discussion Statistical Inference Big Picture R. E. Kass
2011/7/5
Kass states (page 5) that Figure 3 is not a good general description of statistical inference and that Figure 1 is more accurate. I completely agree. Kass states (page 5) that “It is important for stu...
Discussion of "Statistical Inference: The Big Picture" by R. E. Kass
Discussion Statistical Inference The Big Picture R. E. Kass
2011/7/5
In this piece, Rob Kass brings to bear his insights from a long career in both theoretical and applied statistics to reflect on the disconnect between what we teach and what we do.
Statistical Inference: The Big Picture
Bayesian confidence frequentist statistical education
2011/7/5
Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results?
We investigate statistical inference across time scales. We take as toy model the estimation of the intensity of a discretely observed compound Poisson process with symmetric Bernoulli jumps.
Dempster--Shafer Theory and Statistical Inference with Weak Beliefs
Bayesian belief functions fiducial argument frequentist hypothesis testing inferential model
2010/11/9
The Dempster–Shafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence.DS theory has been widely used in computer science and engineering appl...
Statistical inference for multidimensional time-changed Lévy processes based on low-frequency data
time-changed Levy processes dependence minimax rates of convergence lowfrequency observations
2010/3/11
In this article we study the problem of a semi-parametric inference on the parameters of
a multidimensional L´evy process Lt based on the low-frequency observations of the corresponding
time-c...
Statistical inference from set-valued observations
Statistical inference set-valued observations
2009/9/22
Consider a random experiment whose true (unknown)
outcome is modelled by a certain random element X and the available
imprecise observations are modelled by some random set A such that
XE A almost ...