A general Monte Carlo method for multivariate goodness–of–fit testing applied to elliptical families
نویسندگان
چکیده
A general and relatively simple method for construction of multivariate goodness-of-fit tests is introduced. The proposed test applied to elliptical distributions. based on a characterization probability distributions via their characteristic function. consistency other limit properties the new statistics are studied. Also in simulation study compared with earlier as well more recent competitors.
منابع مشابه
A Monte Carlo Method for Integration of Multivariate Smooth Functions
We study a Monte Carlo algorithm that is based on a specific (randomly shifted and dilated) lattice point set. The main result of this paper is that the mean squared error for a given compactly supported, square-integrable function is bounded by n times the L2-norm of the Fourier transform outside a region around the origin, where n is the expected number of function evaluations. As corollaries...
متن کاملA general method for debiasing a Monte Carlo estimator
Consider a stochastic process Xn, n = 0, 1, 2, ...such that EXn → x∞ as n → ∞. The sequence {Xn} may be a deterministic one, obtained by using a numerical integration scheme, or obtained from Monte-Carlo methods involving an approximation to an integral, or a Newton-Raphson iteration to approximate the root of an equation but we will assume that we can sample from the distribution of X1, X2, .....
متن کاملKinetic Monte Carlo method applied to nucleic acid hairpin folding.
Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure, is advantageous for being able to access behavior at long time scales, even minutes or hours. Transition rates between coarse-grained states depend upon intermediate barriers, which are not directly simulated. We propose an Arrhenius rate model and an intermediate energy model that incorporates the effects ...
متن کاملLinUCB Applied to Monte-Carlo Tree Search
UCT is a standard method of Monte Carlo tree search (MCTS) algorithms, which have been applied to various domains and have achieved remarkable success. This study proposes a family of LinUCT algorithms that incorporate LinUCB into MCTS algorithms. LinUCB is a recently developed method that generalizes past episodes by ridge regression with feature vectors and rewards. LinUCB outperforms UCB1 in...
متن کاملConstrained-realization Monte-carlo Method for Hypothesis Testing
We compare two theoretically distinct approaches to generating artii-cial (or \surrogate") data for testing hypotheses about a given data set. The rst and more straightforward approach is to t a single \best" model to the original data, and then to generate surrogate data sets that are \typical realizations" of that model. The second approach concentrates not on the model but directly on the or...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2022
ISSN: ['0167-9473', '1872-7352']
DOI: https://doi.org/10.1016/j.csda.2022.107548