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The 4th International Workshop on Statistical Modeling of Heavy-Tail Phenomena with Applications
The 4th International Workshop Statistical Modeling of Heavy-Tail Phenomena with Applications
2017/12/20
Heavy-tailed distribution theory, alongside with extreme value theory, provide a framework and an indispensable set of tools aiming to analyze the data's atypical behaviors. The eld is driven by and ...
Two modeling strategies for empirical Bayes estimation
f-modeling g-modeling Bayes rule in terms of f
2015/8/20
Empirical Bayes methods use the data from parallel experiments, for instance observtions Xk N (k;1) for k = 1;2; : : : ; N, to estimate the conditional distributions kjXk.
There are two main estima...
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Polygenic Modeling Bayesian Sparse Linear Mixed Models
2012/11/23
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. These two approaches ...
Modeling high-frequency financial data by pure jump processes
Diffusion pure jump process semi-martingales high-frequency data hypothesis testing
2012/6/21
It is generally accepted that the asset price processes contain jumps. In fact, pure jump models have been widely used to model asset prices and/or stochastic volatilities. The question is: is there a...
Factor modeling for high-dimensional time series: Inference for the number of factors
Autocovariance matrices blessing of dimensionality eigenanalysis fast convergence rates multivariate time series
2012/6/19
This paper deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. Under stationary settings, the inference is simple in the sense that both the numbe...