Search results for "Generalized linear model"
showing 10 items of 40 documents
Model averaging estimation of generalized linear models with imputed covariates
2015
a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…
Evaluation of Roundabout Safety Performance through Surrogate Safety Measures from Microsimulation
2018
The paper presents a microsimulation-based approach for roundabout safety performance evaluation. Based on a sample of Slovenian roundabouts, the vehicle trajectories exported from AIMSUN and VISSIM were used to estimate traffic conflicts using the Surrogate Safety Assessment Model (SSAM). AIMSUN and VISSIM were calibrated for single-lane, double-lane and turbo roundabouts using the corresponding empirical capacity function which included critical and follow-up headways estimated through meta-analysis. Based on calibration of the microsimulation models, a crash prediction model from simulated peak hour conflicts for a sample of Slovenian roundabouts was developed. A generalized linear model…
Weighted-average least squares estimation of generalized linear models
2018
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate t…
Using the dglars Package to Estimate a Sparse Generalized Linear Model
2015
dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve. dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, call…
2020
Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…
Understanding german fdi in latin america and asia: a comparison of glm estimators
2020
The growth of Foreign Direct Investment (FDI) in developing countries over the last decade has attracted an intense academic and policy-oriented interest for its determinants. Despite the gravity model being considered a useful tool to approximate bilateral FDI flows, the literature has seen a growing debate in relation to its econometric specification, so that which is the best estimator for the gravity equation is far from conclusive. This paper examines the determinants of German outward FDI in Latin America and Asia for the period 1996-2012 by evaluating the performance of alternative Generalized Linear Model (GLM) estimators. Our findings indicate that Negative Binomial Pseudo Maximum …
Accounting for dispersion and correlation in estimating Safety Performance Functions. An overview starting from a case study
2013
In statistical analysis of crash count data, as well as in estimating Safety Performance Functions (SPFs), the failure of Poisson equidispersion hypothesis and the temporal correlation in annual crash counts must be considered to improve the reliability of estimation of the parameters. After a short discussion on the statistical tools accounting for dispersion and correlation, the paper presents the methodological path followed in estimating a SPF for urban four-leg, signalized intersections. Since the case study exhibited signs of underdispersion, a Conway-Maxwell-Poisson Generalized Linear Model (GLM) was fitted to the data; then a quasi-Poisson model in the framework of Generalized Estim…
Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects
2021
Jyväskylästä kirjoitettiin: Käyn läpi Extra-Vipusessa ristiriitaisiksi luokitettuja yhteisjulkaisuja. Julkaisu " Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects" on meillä laitettu A2 ja teillä A1. Meillä varmaan päädytty tuohon A2:een kun tiivistelmässä sanotaan "Building on a systematic review of six leading management journals..". Mutta mitä mieltä olette, kumpi olisi parempi? Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressing the topic, either directly or indirectly, have been published in the rec…
Revealing Hidden Curvilinear Relations Between Work Engagement and Its Predictors: Demonstrating the Added Value of Generalized Additive Model (GAM)
2014
Previous studies measuring different aspects of the quality of life have, as a rule, presumed linear relationships between a dependent variable and its predictors. This article utilizes non-parametric statistical methodology to explore curvilinear relations between work engagement and its main predictors: job demands, job control and social support. Firstly, the study examines what additional information non-linear modeling can reveal regarding the relationship between work engagement and the three predictors in question. Secondly, the article compares the explanatory power of non-linear and linear modeling with regard to work engagement. The generalized additive model (GAM), that makes pos…
An efficient algorithm to estimate the sparse group structure of an high-dimensional generalized linear model
2014
Massive regression is one of the new frontiers of computational statistics. In this paper we propose a generalization of the group least angle regression method based on the differential geometrical structure of a generalized linear model specified by a fixed and known group structure of the predictors. An efficient algorithm is also proposed to compute the proposed solution curve.