Results 1 to 10 of about 44,938 (219)

Categorical Data Analysis Using a Skewed Weibull Regression Model [PDF]

Entropy, 2018
In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log–
Renault Caron, Debajyoti Sinha, Dipak K. Dey, Adriano Polpo   +3 more
doaj   +7 more sources

New bounded unit Weibull model: Applications with quantile regression [PDF]

PLoS ONE
In practical scenarios, data measurements like ratios and proportions often fall within the 0 to 1 range, posing unique modeling challenges. While beta and Kumaraswamy distributions are widely used, alternative models often yield better performance ...
Laxmi Prasad Sapkota, Nirajan Bam, Vijay Kumar   +2 more
doaj   +4 more sources

Inverted Weibull Regression Models and Their Applications [PDF]

Stats, 2021
In this paper, we propose the classical and Bayesian regression models for use in conjunction with the inverted Weibull (IW) distribution; there are the inverted Weibull Regression model (IW-Reg) and inverted Weibull Bayesian regression model (IW-BReg ...
Sarah R. Al-Dawsari, Khalaf S. Sultan
doaj   +2 more sources

Modeling the hospitalization time of stroke patients at Abdul Wahab Sjahranie Hospital Samarinda using the Weibull Regression Model [PDF]

MethodsX
The Weibull regression model is a regression model derived from the Weibull distribution, where the Weibull distribution is influenced by covariates. In this study, parameter estimation for the Weibull regression model was conducted using the Maximum ...
Suyitno, Darnah, Andrea Tri Rian Dani, Nurul Tri Oktavia   +3 more
doaj   +2 more sources

Stratified Weibull Regression Model for Interval-Censored Data. [PDF]

R J, 2014
Interval censored outcomes arise when a silent event of interest is known to have occurred within a specific time period determined by the times of the last negative and first positive diagnostic tests. There is a rich literature on parametric and non-parametric approaches for the analysis of interval-censored outcomes.
Gu X, Shapiro D, Hughes MD, Balasubramanian R.   +3 more
europepmc   +4 more sources

Parametric regression model for survival data: Weibull regression model as an example. [PDF]

Ann Transl Med, 2016
Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model.
Zhang Z.
europepmc   +4 more sources

Regression Analysis of Cure Model with Generalised Weibull Distribution

Statistica, 2021
Cure models are of special attention when all of the study subjects do not experience the event of interest even after long follow-up time. Many researchers have used exponential, gamma and Weibull distribution in the latency part of parametric cure ...
Parassery Parameswaran Rejani, Paduthol Godan Sankaran   +1 more
doaj   +3 more sources

Geographically weighted Weibull regression modeling on dissolved oxygen data to analyze river water quality in East Kalimantan [PDF]

MethodsX
This study introduces the Geographically Weighted Weibull Regression (GWWR) model as an extension of the Weibull regression (WR) within the geographically weighted regression framework and applies it to spatial environmental data on dissolved oxygen (DO)
Suyitno Suyitno, Darnah, Memi Nor Hayati, Andrea Tri Rian Dani, Ika Purnamasari, Rito Goejantoro, Meiliyani Siringoringo, Pratama Yuly Nugraha, Meirinda Fauziyah, Zabrina Nathania Fauziyah, Mislan   +10 more
doaj   +2 more sources

Correlated Weibull regression model for multivariate binary data [PDF]

, 2002
The correlated Weibull regression model for the analysis of correlated binary data is presented. This regression model is based on Bonney’s disposition model for the regression analysis of correlated binary outcomes. Parameter estimation was done through
Bonney, George E., Joachim, Kötting, Kwagyan, John, Odai, Reginald N. O., Urfer, Wolfgang   +4 more
core   +5 more sources

Bayesian estimation for median discrete Weibull regression model

AIMS Mathematics
The discrete Weibull model can be adapted to capture different levels of dispersion in the count data. This paper takes into account the direct relationship between explanatory variables and the median of discrete Weibull response variable. Additionally,
Monthira Duangsaphon, Sukit Sokampang, Kannat Na Bangchang   +2 more
doaj   +2 more sources