Raphaël Nedellec
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View article: <b>qgam</b>: Bayesian Nonparametric Quantile Regression Modeling in <i>R</i>
<b>qgam</b>: Bayesian Nonparametric Quantile Regression Modeling in <i>R</i> Open
Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package. While the GAM methods provided by mgcv are based on the as…
View article: Interactive anomaly detection in mixed tabular data using Bayesian networks
Interactive anomaly detection in mixed tabular data using Bayesian networks Open
The last decades improvements in processing abilities have quickly led to an increasing use of data analyses implying massive data-sets. To retrieve insightful information from any data driven approach, a pivotal aspect to ensure is good d…
View article: qgam: Bayesian non-parametric quantile regression modelling in R
qgam: Bayesian non-parametric quantile regression modelling in R Open
Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package. While the GAM methods provided by mgcv are based on the as…
View article: Fast Calibrated Additive Quantile Regression
Fast Calibrated Additive Quantile Regression Open
We propose a novel framework for fitting additive quantile regression models, which provides well-calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diver…
View article: Scalable Visualization Methods for Modern Generalized Additive Models
Scalable Visualization Methods for Modern Generalized Additive Models Open
In the last two decades, the growth of computational resources has made it possible to handle generalized additive models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been m…
View article: Scalable visualisation methods for modern Generalized Additive Models
Scalable visualisation methods for modern Generalized Additive Models Open
In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been ma…
View article: Scalable visualisation methods for modern Generalized Additive Models
Scalable visualisation methods for modern Generalized Additive Models Open
In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been ma…