English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Monte Carlo method is a broad class of computational algorithms that rely onrepeated random sampling to obtain numerical results. They are often used inphysical and mathematical problems and are most useful when it is difficult orimpossible to use other mathematical methods. Basically, many statisticianshave been increasingly drawn to Monte Carlo method in three distinct problemclasses: optimization, numerical integration, and generating draws from aprobability distribution. In this paper, we will introduce the Monte Carlomethod for calculating coefficients in Generalized Linear Model(GLM),especially for Logistic Regression. Our main methods are MetropolisHastings(MH) Algorithms and Stochastic Approximation in Monte CarloComputation(SAMC). For comparison, we also get results automatically using MLEmethod in R software.

The application of Monte Carlo methods for learning generalized linear model