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Law of large numbers for branching symmetric Hunt processes with measure-valued branching rates
Law of large numbers branching Hunt processes spine approach h-transform spectral gap
2016/1/26
We establish weak and strong law of large numbers for a class of branching symmetric Hunt processes with the branching rate being a smooth measure with respect to the underlying Hunt process, and the ...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/26
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Central Limit Theorems for Supercritical Branching Nonsymmetric Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale
2016/1/25
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
Central Limit Theorems for Supercritical Branching Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale eigenfunction expansion
2016/1/25
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/25
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Small Value Probabilities for Supercritical Branching Processes with Immigration
Supercritical Galton-Watson branching process small value probability immigration
2016/1/25
We consider a supercritical Galton-Watson branching process with immigration. It is well known that under suitable conditions on the offspring and immigration distributions, there is a finite,strictly...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/25
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/20
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Central Limit Theorems for Supercritical Branching Nonsymmetric Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale
2016/1/20
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
Conditional limit theorems for critical continous-state branching processes
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/20
In this paper we study the conditional limit theorems for critical continuous-state branching processes with branching mechanism ψ(λ) = λ 1+α L(1/λ)where α ∈ [0,1] and L is slowly varying at ∞. We pro...
Central Limit Theorems for Supercritical Branching Markov Processes
Central limit theorem branching Markov process supercritical
2016/1/20
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/20
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Small Value Probabilities for Supercritical Branching Processes with Immigration
Supercritical Galton-Watson branching process small value probability immigration
2016/1/20
We consider a supercritical Galton-Watson branching process with immigration. It is well known that under suitable conditions on the offspring and immigration distributions, there is a finite,strictly...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/20
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
A Strong Law of Large Numbers for Super-stable Processes
Strong Law Large Numbers Super-stable Processes
2016/1/20
A Strong Law of Large Numbers for Super-stable Processes.