Results 231 to 240 of about 31,221,148 (284)

Inference via the Skewness‐Kurtosis Set

open access: yesInternational Statistical Review, EarlyView.
Summary Kurtosis minus squared skewness is bounded from below by 1, but for unimodal distributions, this parameter is bounded by 189/125. In some applications, it is natural to compare distributions by comparing their kurtosis‐minus‐squared‐skewness parameters. The asymptotic behavior of the empirical version of this parameter is studied here for i.i.d.
Chris A. J. Klaassen, Bert van Es
wiley   +1 more source

Federated Random Forest on Non-IID Data

open access: yesKIISE Transactions on Computing Practices
Penjan Antonio Eng Lim, Cheong-Hee Park
openaire   +1 more source

On Spatial Point Processes With Composition‐Valued Marks

open access: yesInternational Statistical Review, EarlyView.
Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt   +2 more
wiley   +1 more source

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

open access: yesInternational 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   +3 more
wiley   +1 more source

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

open access: yesInternational 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   +3 more
wiley   +1 more source

On Integral Priors for Multiple Comparison in Bayesian Model Selection

open access: yesInternational Statistical Review, EarlyView.
Summary Noninformative priors constructed for estimation purposes are usually not appropriate for model selection and testing. The methodology of integral priors was developed to get prior distributions for Bayesian model selection when comparing two models, modifying initial improper reference priors. We propose a generalisation of this methodology to
Diego Salmerón   +2 more
wiley   +1 more source

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