Results 21 to 30 of about 134,460 (206)

Statistical model assumptions achieved by linear models: classics and generalized mixed

Revista Ciência Agronômica, 2020
When an agricultural experiment is completed and the data about the response variable is available, it is necessary to perform an analysis of variance.
Rita Carolina de Melo, Nicole Trevisani, Marcio dos Santos, Altamir Frederico Guidolin, Jefferson Luís Meirelles Coimbra   +4 more
doaj   +1 more source

Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships

Mathematics, 2021
Our article explores an underused mathematical analytical methodology in the social sciences. In addition to describing the method and its advantages, we extend a previously reported application of mixed models in a well-known database about corruption ...
Luiz Paulo Fávero, Joseph F. Hair, Rafael de Freitas Souza, Matheus Albergaria, Talles V. Brugni   +4 more
doaj   +1 more source

Macro vs. Micro Methods in Non-Life Claims Reserving (an Econometric Perspective)

Risks, 2016
Traditionally, actuaries have used run-off triangles to estimate reserve (“macro” models, on aggregated data). However, it is possible to model payments related to individual claims. If those models provide similar estimations, we investigate uncertainty
Arthur Charpentier, Mathieu Pigeon
doaj   +1 more source

Using linear mixed model and dummy variable model approaches to construct compatible single-tree biomass equations at different scales - A case study for Masson pine in Southern China

Journal of Forest Science, 2012
The estimation of forest biomass is important for practical issues and scientific purposes in forestry. The estimation of forest biomass on a large-scale level would be merely possible with the application of generalized single-tree biomass models.
L.Y. Fu, W.S. Zeng, S.Z. Tang, R.P. Sharma, H.K. Li   +4 more
doaj   +1 more source

Half-Normal Plots and Overdispersed Models in R: The hnp Package

Journal of Statistical Software, 2017
Count and proportion data may present overdispersion, i.e., greater variability than expected by the Poisson and binomial models, respectively. Different extended generalized linear models that allow for overdispersion may be used to analyze this type of
Rafael A Moral, John Hinde, Clarice G B Demétrio   +2 more
doaj   +1 more source

Estimating Territory Risk Relativity Using Generalized Linear Mixed Models and Fuzzy C-Means Clustering

Risks, 2023
Territory risk analysis has played an important role in auto insurance rate regulation. It aims to design rating territories from a set of basic rating units so that their respective risk relativities can be estimated to reflect the regional risk of ...
Shengkun Xie, Chong Gan
doaj   +1 more source

Multivariate Generalized Linear Mixed Models for Count Data

Austrian Journal of Statistics
Univariate regression models have rich literature for counting data. However, this is not the case for multivariate count data. Therefore, we present the Multivariate Generalized Linear Mixed Models framework that deals with a multivariate set of ...
Guilherme Parreira da Silva, Henrique Aparecido Laureano, Ricardo Rasmussen Petterle, Paulo Justiniano Ribeiro Júnior, Wagner Hugo Bonat   +4 more
doaj   +1 more source

mplot: An R Package for Graphical Model Stability and Variable Selection Procedures

Journal of Statistical Software, 2018
The mplot package provides an easy to use implementation of model stability and variable inclusion plots (Müller and Welsh 2010; Murray, Heritier, and Müller 2013) as well as the adaptive fence (Jiang, Rao, Gu, and Nguyen 2008; Jiang, Nguyen, and Rao ...
Garth Tarr, Samuel Müller, Alan H. Welsh   +2 more
doaj   +1 more source

Bambi: A Simple Interface for Fitting Bayesian Linear Models in Python

Journal of Statistical Software, 2022
The popularity of Bayesian statistical methods has increased dramatically in recent years across many research areas and industrial applications. This is the result of a variety of methodological advances with faster and cheaper hardware as well as the ...
Tomás Capretto, Camen Piho, Ravin Kumar, Jacob Westfall, Tal Yarkoni, Osvaldo A Martin   +5 more
doaj   +1 more source

Social Functioning Within the First Years After Pediatric Brain Tumor Diagnosis and the Relationship With Family Psychosocial Risk

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survivors of pediatric brain tumors (PBTs) can experience long‐term social difficulties, impacting quality of life. Beyond medical and environmental factors, family psychosocial risk may play a role in social outcomes by shaping the caregiving environment and may provide intervention options.
Renske H. Houben, Marisa H. Huisman, Martha A. Grootenhuis, Femke K. Aarsen, Marita Partanen   +4 more
wiley   +1 more source