Results 61 to 70 of about 4,846 (159)

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

Cryptocurrency Bubbles and Costly Mining

International Economic Review, EarlyView.
ABSTRACT This paper develops a model of a cryptocurrency by incorporating mining into the otherwise standard search‐theoretic monetary framework. As usual, multiple equilibria exist. To obtain a sharp prediction on whether a cryptocurrency' s value will last in the future, I propose a notion of equilibrium refinement based on the feature that mining ...
Kohei Iwasaki
wiley   +1 more source

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels

International Statistical Review, EarlyView.
Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing, Michail Papathomas, Silvia Liverani   +2 more
wiley   +1 more source

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

International Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula Moraga   +2 more
wiley   +1 more source

Specification Tests for Jump‐Diffusion Models Based on the Characteristic Function

International Statistical Review, EarlyView.
Summary Goodness‐of‐fit tests are suggested for several popular jump‐diffusion processes. The suggested test statistics utilise the marginal characteristic function of the model and its L2‐type discrepancy from an empirical counterpart. Model parameters are estimated either by minimising the aforementioned L2‐type discrepancy or by maximum likelihood ...
Gerrit Lodewicus Grobler, Denis Belomestny, Simos George Meintanis, Emanuele Taufer   +3 more
wiley   +1 more source

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, EarlyView.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Optimal Simple Ratings

The Journal of Industrial Economics, EarlyView.
ABSTRACT We study optimal simple rating systems that partition sellers into a finite number of tiers. We show that optimal ratings must be threshold partitions, and that for linear supply and Cournot competition with constant marginal cost, optimal thresholds solve a k‐means clustering problem requiring only the quality distribution.
Hugo Hopenhayn, Maryam Saeedi
wiley   +1 more source

Bayesian Analysis of Discrete Skewed Laplace Distribution

Journal of Modern Applied Statistical Methods, 2016
A. Hossianzade, K. Zare
openaire   +2 more sources

Markov Determinantal Point Process for Dynamic Random Sets

Journal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source