An identification method to calibrate higher-order parameters in local second-gradient models

Higher-order dependencies in local appearance models

We propose a novel local appearance modeling method for object detection and recognition in cluttered scenes. The approach is based on the joint distribution of local feature vectors at multiple salient points and factorization with Independent Component Analysis (ICA). The resulting densities are simple multiplicative distributions modeled through adaptative Gaussian mixture models. This leads...

Objective Bayesian higher-order asymptotics in models with nuisance parameters

We discuss higher-order approximations to the marginal posterior distribution for a scalar parameter of interest in the presence of nuisance parameters. These higher-order approximations are obtained using a suitable matching prior. The proposed procedure has several advantages since it does not require the elicitation on the nuisance parameter, neither numerical integration or MCMC simulation,...

Smooth Isotonic Regression: A New Method to Calibrate Predictive Models

Predictive models are critical for risk adjustment in clinical research. Evaluation of supervised learning models often focuses on predictive model discrimination, sometimes neglecting the assessment of their calibration. Recent research in machine learning has shown the benefits of calibrating predictive models, which becomes especially important when probability estimates are used for clinica...

Identification of multichannel MA parameters using higher-order statistics

Fitting Second-order Models to Mixed Two-level and Four-level Factorial Designs: Is There an Easier Procedure?

Fitting response surface models is usually carried out using statistical packages to solve complicated equations in order to produce the estimates of the model coefficients. This paper proposes a new procedure for fitting response surface models to mixed two-level and four-level factorial designs. New and easier formulae are suggested to calculate the linear, quadratic and the interaction coeff...