This paper describes a new approach to adaptive estimation of parametric deformable contours based on B-spline representations. The problem is formulated in a statistical framework with the likelihood function being derived from a region-based image model. The parameters of the image model, the contour parameters, and the B-spline parameterization order (i.e., the number of control points) are ...

Wavelet-based analysis versus Gaussian smoothing in statistical parametric mapping (SPM) for detecting and analyzing brain activity from functional magnetic resonance imaging (fMRI) data is presented. Detection of activation in fMRI data can be performed in the wavelet domain by a coefficient-wise statistical t-test. The link between the wavelet analysis and SPM is based on two observations: (i...

When several data owners possess data on different records but the same variables, known as horizontally partitioned data, the owners can improve statistical inferences by sharing their data with each other. Often, however, the owners are unwilling or unable to share because the data are confidential or proprietary. Secure computation protocols enable the owners to compute parameter estimates f...

When several data owners possess data on different records but the same variables, known as horizontally partitioned data, the owners can improve statistical inferences by sharing their data with each other. Often, however, the owners are unwilling or unable to share because the data are confidential or proprietary. Secure computation protocols enable the owners to compute parameter estimates f...

The objective of this study is to propose a statistical modeling method which enables simultaneous term structure estimation of the risk-free interest rate, hazard and loss given default, incorporating the characteristics of the bond issuing company such as credit rating and financial information. A reduced form model is used for this purpose. Statistical techniques such as spline estimation an...

introduction studies about the health effects of long-term average exposure to outdoor air pollution have played an important role in the recent health impact assessments. exposure assessment for epidemiological studies of long-term exposure to ambient air pollution remains a difficult challenge because of substantial small-scale spatial variation. current approaches for assessing intra-urban ai...

We review the current state of nonparametric Bayesian inference. The discussion follows a list of important statistical inference problems, including density estimation, regression, survival analysis, hierarchical models and model validation. For each inference problem we review relevant nonparametric Bayesian models and approaches including Dirichlet process (DP) models and variations, Polya t...

This research deals with the use of a number statistical methods, such as kernel method, watershed, histogram, and cubic spline, to improve contrast digital images. The results obtained according RSME NCC standards have proven that spline method is most accurate in compared other methods.