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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In certain cases, often encountered a group of data where the observed respone variable shaped non-negative and not symmetrical (skewed to the right). The case data such as this one can be found in the field of insurance, such as variable stating the amount of claims or states of time between when a customer claims to obtain these claims. To handle such cases one of them is by using a generalized linear model, with respone variables that follow the gamma distribution. The paper discusses the inspection data outliers and influential data in the modeling of the respone following the gamma distribution. Several statistical measures used to examine the outlier data is the value of leverage, standardized deviance residual, standardized Pearson residual, and residual likelihood. Then the data outliers potentially influential data will be examined using Cook's distance statistics. Keywords : Gamma Distributions, Leverage, Standardized Deviance Residual, Standardized Pearson Residual, And Residual Likelihood, Cook's Distance Statistics

PEMERIKSAAN DATA BERPENGARUH DALAM MODEL REGRESI GAMMA